Monitoring Start of Season in Alaska

NASA Astrophysics Data System (ADS)

Robin, J.; Dubayah, R.; Sparrow, E.; Levine, E.

2006-12-01

In biomes that have distinct winter seasons, start of spring phenological events, specifically timing of budburst and green-up of leaves, coincides with transpiration. Seasons leave annual signatures that reflect the dynamic nature of the hydrologic cycle and link the different spheres of the Earth system. This paper evaluates whether continuity between AVHRR and MODIS normalized difference vegetation index (NDVI) is achievable for monitoring land surface phenology, specifically start of season (SOS), in Alaska. Additionally, two thresholds, one based on NDVI and the other on accumulated growing degree-days (GDD), are compared to determine which most accurately predicts SOS for Fairbanks. Ratio of maximum greenness at SOS was computed from biweekly AVHRR and MODIS composites for 2001 through 2004 for Anchorage and Fairbanks regions. SOS dates were determined from annual green-up observations made by GLOBE students. Results showed that different processing as well as spectral characteristics of each sensor restrict continuity between the two datasets. MODIS values were consistently higher and had less inter-annual variability during the height of the growing season than corresponding AVHRR values. Furthermore, a threshold of 131-175 accumulated GDD was a better predictor of SOS for Fairbanks than a NDVI threshold applied to AVHRR and MODIS datasets. The NDVI threshold was developed from biweekly AVHRR composites from 1982 through 2004 and corresponding annual green-up observations at University of Alaska-Fairbanks (UAF). The GDD threshold was developed from 20+ years of historic daily mean air temperature data and the same green-up observations. SOS dates computed with the GDD threshold most closely resembled actual green-up dates observed by GLOBE students and UAF researchers. Overall, biweekly composites and effects of clouds, snow, and conifers limit the ability of NDVI to monitor phenological changes in Alaska.

Water vapour correction of the daily 1 km AVHRR global land dataset: Part I validation and use of the Water Vapour input field

USGS Publications Warehouse

DeFelice, Thomas P.; Lloyd, D.; Meyer, D.J.; Baltzer, T. T.; Piraina, P.

2003-01-01

An atmospheric correction algorithm developed for the 1 km Advanced Very High Resolution Radiometer (AVHRR) global land dataset was modified to include a near real-time total column water vapour data input field to account for the natural variability of atmospheric water vapour. The real-time data input field used for this study is the Television and Infrared Observational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder A global total column water vapour dataset. It was validated prior to its use in the AVHRR atmospheric correction process using two North American AVHRR scenes, namely 13 June and 28 November 1996. The validation results are consistent with those reported by others and entail a comparison between TOVS, radiosonde, experimental sounding, microwave radiometer, and data from a hand-held sunphotometer. The use of this data layer as input to the AVHRR atmospheric correction process is discussed.

The 1990 conterminous U. S. AVHRR data set

USGS Publications Warehouse

Eidenshink, Jeffery C.

1992-01-01

The U.S. Geological Survey, using NOAA-ll Advanced Very High Resolution Radiometer (AVHRR) 1-km data, has produced a time series of 19 biweekly maximum normalized difference vegetation index (NDV!) composites of the conterminous United States for the 1990 growing season. Each biweekly composite included data from approximately 20 calibrated and georegistered daily overpasses. The output is a data set which includes all five calibrated AVHRR channels, NOV! values, three satellite/solar viewing angles, and date of observation pointer for each biweekly composite. The data set is intended for assessing seasonal variations in vegetation condition and provides a foundation for studying long-term changes in vegetation resulting from human interactions or global climate alterations.

The utility of estimating net primary productivity over Alaska using baseline AVHRR data

USGS Publications Warehouse

Markon, C.J.; Peterson, Kim M.

2002-01-01

Net primary productivity (NPP) is a fundamental ecological variable that provides information about the health and status of vegetation communities. The Normalized Difference Vegetation Index, or NDVI, derived from the Advanced Very High Resolution Radiometer (AVHRR) is increasingly being used to model or predict NPP, especially over large remote areas. In this article, seven seasonally based metrics calculated from a seven-year baseline NDVI dataset were used to model NPP over Alaska, USA. For each growing season, they included maximum, mean and summed NDVI, total days, product of total days and maximum NDVI, an integral estimate of NDVI and a summed product of NDVI and solar radiation. Field (plot) derived NPP estimates were assigned to 18 land cover classes from an Alaskan statewide land cover database. Linear relationships between NPP and each NDVI metric were analysed at four scales: plot, 1-km, 10-km and 20-km pixels. Results show moderate to poor relationship between any of the metrics and NPP estimates for all data sets and scales. Use of NDVI for estimating NPP may be possible, but caution is required due to data seasonality, the scaling process used and land surface heterogeneity.

a New Algorithm for the Aod Inversion from Noaa/avhrr Data

NASA Astrophysics Data System (ADS)

Sun, L.; Li, R.; Yu, H.

2018-04-01

The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74 % of the retrieved AOD are within the expected error range of ±(0.05 + 0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

Investigations of possible contributions NDVI's have to misclassification in AVHRR data analysis

Treesearch

David L. Evans; Raymond L. Czaplewski

1996-01-01

Numerous subcontinental-scale projects have placed significant emphasis on the use of Normalized Difference Vegetation Indices (NDVI's) derived from Advanced Very High Resolution Radiometer (AVHRR) satellite data for vegetation type recognition. In multi-season AVHRR data, overlap of NDVI ranges for vegetation classes may degrade overall classification performance...

Using NOAA AVHRR data to assess flood damage in China.

PubMed

Wang, Quan; Watanabe, Masataka; Hayashi, Seiji; Murakami, Shogo

2003-03-01

The article used two NOAA-14 Advanced Very High Resolution Radiometer (AVHRR) datasets to assess flood damage in the middle and lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetrate the clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, since water has a much lower NDVI value than other surface features. Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished from other types of ground cover by changes in the NDVI value before and after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 were selected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs, and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculated for cloud-free pixels. The difference in the NDVI values between these two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the area lost to the flood. The results show a total of 358,867 ha, with 207,556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321,000 and 197,000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensing data (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded region in the

Analysis of forest disturbance using TM and AVHRR data

NASA Technical Reports Server (NTRS)

Spanner, Michael A.; Hlavka, Christine A.; Pierce, Lars L.

1989-01-01

A methodology that will be used to determine the proportions of undisturbed, successional vegetation and recently disturbed land cover within coniferous forests using remotely sensed data from the advanced very high resolution radiometer (AVHRR) is presented. The method uses thematic mapper (TM) data to determine the proportions of the three stages of forest disturbance and regrowth for each AVHRR pixel in the sample areas, and is then applied to interpret all AVHRR imagery. Preliminary results indicate that there are predictable relationships between TM spectral response and the disturbance classes. Analysis of ellipse plots from a TM classification of the disturbed forested landscape indicates that the forest classes are separable in the red (0.63-0.69 micron) and near-infrared (0.76-0.90 micron) bands, providing evidence that the proportion of disturbance classes may be determined from AVHRR data.

A RESEARCH PLAN FOR THE USE OF THERMAL AVHRR IMAGERY TO STUDY ANNUAL AND SEASONAL MEAN SURFACE TEMPERATURES FOR LARGE LAKES IN NORTH AMERICA

EPA Science Inventory

Surface and vertical temperature data will be obtained from several large lakes With surface areas large enough to be effectively sampled with AVHRR imagery. Yearly and seasonal patterns of surface and whole water column thermal values will be compared to estimates of surface tem...

Comparison of MODIS and AVHRR 16-day normalized difference vegetation index composite data

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei; Reed, Bradley C.; Dwyer, John L.; Eidenshink, Jeffery C.

2004-01-01

Normalized difference vegetation index (NDVI) data derived from visible and near-infrared data acquired by the MODIS and AVHRR sensors were compared over the same time periods and a variety of land cover classes within the conterminous USA. The relationship between the AVHRR derived NDVI values and those of future sensors is critical to continued long term monitoring of land surface properties. The results indicate that the 16-day composite values are quite similar over the 23 intervals of 2001 that were analyzed, and a linear relationship exists between the NDVI values from the two sensors. The composite AVHRR NDVI data were associated with over 90% of the variation in the MODIS NDVI values. Copyright 2004 by the American Geophysical Union.

A Comparison of Seasonal and Interannual Variability of Soil Dust Aerosols Over the Atlantic Ocean as Inferred by the Toms AI and AVHRR AOT Retrievals

NASA Technical Reports Server (NTRS)

Cakmur, R. V.; Miller, R. L.; Tegen, Ina; Hansen, James E. (Technical Monitor)

2001-01-01

The seasonal cycle and interannual variability of two estimates of soil (or 'mineral') dust aerosols are compared: Advanced Very High Resolution Radiometer (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spectrometer (TOMS) aerosol index (AI), Both data sets, comprising more than a decade of global, daily images, are commonly used to evaluate aerosol transport models. The present comparison is based upon monthly averages, constructed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparison focuses upon the Northern Hemisphere subtropical Atlantic Ocean, where soil dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive to a different aerosol radiative property - absorption for the TOMS AI versus reflectance for the AVHRR AOT - the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations in the height of the aerosol layer are taken into account when interpreting the TOMS AI. On interannual time scales, the correlation is low at most locations. It is suggested that the poor interannual correlation is at least partly a consequence of data availability. When the monthly averages are constructed using only days common to both data sets, the correlation is substantially increased: this consistency suggests that both TOMS and AVHRR accurately measure the aerosol load in any given scene. However, the two retrievals have only a few days in common per month so that these restricted monthly averages have a large uncertainty. Calculations suggest that at least 7 to 10 daily images are needed to estimate reliably the average dust load during any particular month, a threshold that is rarely satisfied by the AVHRR AOT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of

Evaluation of AVHRR Aerosol Properties Over Mainland China from Deepblue Algorithm

NASA Astrophysics Data System (ADS)

Xue, Y.; Che, Y.; She, L.

2017-12-01

Advanced Very High Resolution Radiometer (AVHRR) on-board NOAA series satellites is the only operational senor which keeps observing surface of the Earth and cloud over 30 years since 1979. Such long time coverage helps to expand the application of AVHRR to aerosol properties retrieval over both land and ocean successfully. Recently in 2017, the Deep Blue Project has published AVHRR `Deep Blue' dataset version 001 (V001) using `Deep Blue (DB)' algorithm(Sayer et al., 2017). This dataset includes not only aerosol properties over land but also oceanic aerosol product at three periods (NOAA-11: 1989-1990, NOAA-14: 1995-1999, NOAA-18: 2006-2011). We pay much of our attention to DB's performance over mainland China. Therefore, in the presenting paper, we focus on validating AVHRR/DB dataset over different land covers in China in 2007, 2008 and 2010. Both of data from ground-based networks from the Aerosol Robotic NETwork (AERONET) and China Aerosol Remote Sensing Network (CARSNET) are used as reference data. The collocation method is to match data at a time range of of satellite pass-by and at a spatial frame of pixels around ground-based site. Totally, data from 18 AERONET and 25 CARSNET are used as shown in figure, collocating 922 matches with AERONET and 2325 matches with CARSNET. Additionally, we introduced a corrected RMS error as main evaluation metric. As a result, AVHRR/DB underestimates AOD increasingly and more uncertainties and errors will be introduced with the growth of AOD. Otherwise, the performance of AVHRR/DB are better compared with AERONET data than with CARSNET data from RMSbc of 0.35 vs. 0.42. Their Rs (0.757 vs. 0.654) prove this characteristic too. For urban areas, the performances in Beijing are better than that in Xi'an from RMSbc, otherwise RMS in Xi'an (0.324) is lower than others' (0.346 and 0.383) mainly because of small AOD observed range and low R (0.624). For croplands, those performances are at same levels with RMSbc from 0.312 to 0

Senegalese land surface change analysis and biophysical parameter estimation using NOAA AVHRR spectral data

NASA Technical Reports Server (NTRS)

Vukovich, Fred M.; Toll, David L.; Kennard, Ruth L.

1989-01-01

Surface biophysical estimates were derived from analysis of NOAA Advanced Very High Spectral Resolution (AVHRR) spectral data of the Senegalese area of west Africa. The parameters derived were of solar albedo, spectral visible and near-infrared band reflectance, spectral vegetative index, and ground temperature. Wet and dry linked AVHRR scenes from 1981 through 1985 in Senegal were analyzed for a semi-wet southerly site near Tambacounda and a predominantly dry northerly site near Podor. Related problems were studied to convert satellite derived radiance to biophysical estimates of the land surface. Problems studied were associated with sensor miscalibration, atmospheric and aerosol spatial variability, surface anisotropy of reflected radiation, narrow satellite band reflectance to broad solar band conversion, and ground emissivity correction. The middle-infrared reflectance was approximated with a visible AVHRR reflectance for improving solar albedo estimates. In addition, the spectral composition of solar irradiance (direct and diffuse radiation) between major spectral regions (i.e., ultraviolet, visible, near-infrared, and middle-infrared) was found to be insensitive to changes in the clear sky atmospheric optical depth in the narrow band to solar band conversion procedure. Solar albedo derived estimates for both sites were not found to change markedly with significant antecedent precipitation events or correspondingly from increases in green leaf vegetation density. The bright soil/substrate contributed to a high albedo for the dry related scenes, whereas the high internal leaf reflectance in green vegetation canopies in the near-infrared contributed to high solar albedo for the wet related scenes. The relationship between solar albedo and ground temperature was poor, indicating the solar albedo has little control of the ground temperature. The normalized difference vegetation index (NDVI) and the derived visible reflectance were more sensitive to antecedent

Prototype global burnt area algorithm using the AVHRR-LTDR time series

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Pereira, José Miguel; Aires, Filipe

2013-04-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05° spatial resolution and is available for the 1981-1999 time period. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR dataset, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for year 1998, which was selected because of a positive fire anomaly, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Unmixing AVHRR Imagery to Assess Clearcuts and Forest Regrowth in Oregon

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Spanner, Michael A.

1995-01-01

Advanced Very High Resolution Radiometer imagery provides frequent and low-cost coverage of the earth, but its coarse spatial resolution (approx. 1.1 km by 1.1 km) does not lend itself to standard techniques of automated categorization of land cover classes because the pixels are generally mixed; that is, the extent of the pixel includes several land use/cover classes. Unmixing procedures were developed to extract land use/cover class signatures from mixed pixels, using Landsat Thematic Mapper data as a source for the training set, and to estimate fractions of class coverage within pixels. Application of these unmixing procedures to mapping forest clearcuts and regrowth in Oregon indicated that unmixing is a promising approach for mapping major trends in land cover with AVHRR bands 1 and 2. Including thermal bands by unmixing AVHRR bands 1-4 did not lead to significant improvements in accuracy, but experiments with unmixing these four bands did indicate that use of weighted least squares techniques might lead to improvements in other applications of unmixing.

MEDOKADS - A 20 Year's Daily AVHRR Data Series for Analysis of Land Surface Properties

NASA Astrophysics Data System (ADS)

Koslowsky, D.; Billing, H.; Bolle, H.-J.

2009-04-01

To derive primary data products from raw AVHRR data, like spectral reflectances or temperatures, it is necessary to correct for sensor degradation and changing hardware specifications, to re-sample the data into a grid of equal pixel size, to perform geographical registration, cloud-screening and normalization for illumination and observation geometry. A data set which resulted from the application of these corrections is the top of the atmosphere Mediterranean Extended One-Km AVHRR Data Set (MEDOKADS) which now covers a period of 20 years. To study land surface processes, the obtained spectral data have to be combined, radiometric corrections for atmospheric effects, emissivity corrections in the case of temperature measurements have to be applied, and the variable over-flight times have to be accounted for. By application of complex evaluation schemes then higher level products are generated, like vegetation indices, surface albedo, and surface energy fluxes. The ultimate goal is to provide the users community with problem-related information. This includes the quantification of changes and the determination of trends. Methods and tools to reach this goal as well as their limitations are discussed. To validate the data, extended field measurements have been performed in which the scaling between local ground measurements and large scale satellite data play a major role. A major problem remains the application of atmospheric corrections because of the not well known variable aerosol content. The supervision of the quality of the derived information leads to the concept of anchor stations at which surface and atmospheric properties should permanently be measured.

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

NASA Technical Reports Server (NTRS)

Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

1989-01-01

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

Use of NOAA-N satellites for land/water discrimination and flood monitoring

NASA Technical Reports Server (NTRS)

Tappan, G.; Horvath, N. C.; Doraiswamy, P. C.; Engman, T.; Goss, D. W. (Principal Investigator)

1983-01-01

A tool for monitoring the extent of major floods was developed using data collected by the NOAA-6 advanced very high resolution radiometer (AVHRR). A basic understanding of the spectral returns in AVHRR channels 1 and 2 for water, soil, and vegetation was reached using a large number of NOAA-6 scenes from different seasons and geographic locations. A look-up table classifier was developed based on analysis of the reflective channel relationships for each surface feature. The classifier automatically separated land from water and produced classification maps which were registered for a number of acquisitions, including coverage of a major flood on the Parana River of Argentina.

Mapping Fire Scars in the Brazilian Cerrado Using AVHRR Imagery

NASA Technical Reports Server (NTRS)

Hlavka, C. A.; Ambrosia, V. G.; Brass, J. A.; Rezendez, A.; Alexander, S.; Guild, L. S.; Peterson, David L. (Technical Monitor)

1995-01-01

The Brazilian cerrado, or savanna, spans an area of 1,800,000 square kilometers on the great plateau of Central Brazil. Large fires covering hundreds of square kilometers, frequently occur in wildland areas of the cerrado, dominated by grasslands or grasslands mixed with shrubs and small trees, and also within area in the cerrado used for agricultural purposes, particularly for grazing. Smaller fires, typically extending over arm of a few square kilometers or less, are associated with the clewing of crops, such as dry land rice. A method for mapping fire scars and differentiating them from extensive areas of bare sod with AVHRR bands 1 (.55 -.68 micrometer) and 3 (3.5 - 3.9 micrometers) and measures of performance based on comparison with maps of fires with Landsat imagery will be presented. Methods of estimating total area burned from the AVHRR fire scar map will be discussed and related to land use and scar size.

Regional seasonal warming anomalies and land-surface feedbacks

NASA Astrophysics Data System (ADS)

Coffel, E.; Horton, R. M.

2017-12-01

Significant seasonal variations in warming are projected in some regions, especially central Europe, the southeastern U.S., and central South America. Europe in particular may experience up to 2°C more warming during June, July, and August than in the annual mean, enhancing the risk of extreme summertime heat. Previous research has shown that heat waves in Europe and other regions are tied to seasonal soil moisture variations, and that in general land-surface feedbacks have a strong effect on seasonal temperature anomalies. In this study, we show that the seasonal anomalies in warming are also due in part to land-surface feedbacks. We find that in regions with amplified warming during the hot season, surface soil moisture levels generally decline and Bowen ratios increase as a result of a preferential partitioning of incoming energy into sensible vs. latent. The CMIP5 model suite shows significant variability in the strength of land-atmosphere coupling and in projections of future precipitation and soil moisture. Due to the dependence of seasonal warming on land-surface processes, these inter-model variations influence the projected summertime warming amplification and contribute to the uncertainty in projections of future extreme heat.

Polar Geophysics Products Derived from AVHRR: The "AVHRR Polar Pathfinder

NASA Technical Reports Server (NTRS)

Maslanik, James; Fowler, Charles; Scambos, Theodore

1999-01-01

This NOAA/NASA Pathfinder effort was established to locate, acquire, and process Advanced Very High Resolution Radiometer (AVHRR) imagery into geo-located and calibrated radiances, cloud masks, surface clear-sky broadband albedo, clear-sky skin temperatures, satellite viewing times, and viewing and solar geometry for the, high-latitude portions of the northern and southern hemispheres (all area north of 48N and south of 53S). AVHRR GAC data for August 1981 - July 1998 were acquired, with some gaps remaining, and processed into twice-daily 5-km grids, with some products also provided at 25-km resolution. AVHRR LAC data for 3.5 years of coverage in the northern hemisphere and 2.75 years of coverage in the southern hemisphere were processed into 1.25-km grids for the same suite of products. The resulting data sets are presently being transferred to the National Snow and Ice Data Center (NSIDC) for archiving and distribution. Using these data, researchers now have at their disposal an extensive AVHRR data set for investigations of high-latitude processes. In addition, the data lend themselves to development and testing of algorithms. The products are particularly relevant for climate research and algorithm development as applied to relatively long time periods and large areas.

Linkages between Land Surface Phenology Metrics and Natural and Anthropogenic Events in Drylands (Invited)

NASA Astrophysics Data System (ADS)

de Beurs, K.; Brown, M. E.; Ahram, A.; Walker, J.; Henebry, G. M.

2013-12-01

Tracking vegetation dynamics across landscapes using remote sensing, or 'land surface phenology,' is a key mechanism that allows us to understand ecosystem changes. Land surface phenology models rely on vegetation information from remote sensing, such as the datasets derived from the Advanced Very High Resolution Radiometer (AVHRR), the newer MODIS sensors on Aqua and Terra, and sometimes the higher spatial resolution Landsat data. Vegetation index data can aid in the assessment of variables such as the start of season, growing season length and overall growing season productivity. In this talk we use Landsat, MODIS and AVHRR data and derive growing season metrics based on land surface phenology models that couple vegetation indices with satellite derived accumulated growing degreeday and evapotranspiration estimates. We calculate the timing and the height of the peak of the growing season and discuss the linkage of these land surface phenology metrics with natural and anthropogenic changes on the ground in dryland ecosystems. First we will discuss how the land surface phenology metrics link with annual and interannual price fluctuations in 229 markets distributed over Africa. Our results show that there is a significant correlation between the peak height of the growing season and price increases for markets in countries such as Nigeria, Somalia and Niger. We then demonstrate how land surface phenology metrics can improve models of post-conflict resolution in global drylands. We link the Uppsala Conflict Data Program's dataset of political, economic and social factors involved in civil war termination with an NDVI derived phenology metric and the Palmer Drought Severity Index (PDSI). An analysis of 89 individual conflicts in 42 dryland countries (totaling 892 individual country-years of data between 1982 and 2005) revealed that, even accounting for economic and political factors, countries that have higher NDVI growth following conflict have a lower risk of

Long-term record of top-of-atmosphere albedo generated from AVHRR data

NASA Astrophysics Data System (ADS)

Song, Z.

2017-12-01

Top-of-Atmosphere (TOA) albedo is a fundamental component of Earth's energy budget. Previously, long-term accurate TOA albedo products did not exist due to the lack of stable broadband observations. With a new albedo estimation methodology based on multispectral observations, TOA albedo since 1981 has been retrieved using data from the Advanced Very High Resolution Radiometer (AVHRR), which provides the longest record of satellite observations across the globe. To develop the long-term TOA albedo record, the instantaneous TOA albedo was calculated by the direct estimation method, which was built on training data pairs from coincident AVHRR TOA reflectance and Moderate Resolution Imaging Spectroradiometer (MODIS) TOA albedo. The instantaneous TOA albedo was then converted to daily mean and monthly mean albedo based on the diurnal curves from geostationary satellites. The TOA albedo results (AVHRR-TAL) were compared with Clouds and the Earth's Radiant Energy System (CERES) flux products for 2007. The monthly mean AVHRR-TAL agreed well with the CERES products, with a root mean square difference (RMSD) of 0.032 and a bias of 0.013. In addition, AVHRR-TAL showed similar seasonal variations to those seen in the CERES products. Further analysis on long-term time series showed good consistency between the two datasets (R2 > 0.95 and relative RMSD < 4%) from 2000 to 2015. Although some calibration issues remain to be solved, our datasets show the potential ability to observe the global TOA albedo from 1981 to the present.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Development of digital interactive processing system for NOAA satellites AVHRR data

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Murthy, N. N.

The paper discusses the digital image processing system for NOAA/AVHRR data including Land applications - configured around VAX 11/750 host computer supported with FPS 100 Array Processor, Comtal graphic display and HP Plotting devices; wherein the system software for relational Data Base together with query and editing facilities, Man-Machine Interface using form, menu and prompt inputs including validation of user entries for data type and range; preprocessing software for data calibration, Sun-angle correction, Geometric Corrections for Earth curvature effect and Earth rotation offsets and Earth location of AVHRR image have been accomplished. The implemented image enhancement techniques such as grey level stretching, histogram equalization and convolution are discussed. The software implementation details for the computation of vegetative index and normalized vegetative index using NOAA/AVHRR channels 1 and 2 data together with output are presented; scientific background for such computations and obtainability of similar indices from Landsat/MSS data are also included. The paper concludes by specifying the further software developments planned and the progress envisaged in the field of vegetation index studies.

NOAA AVHRR and its uses for rainfall and evapotranspiration monitoring

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Imbernon, J.; Dedieu, G.; Hautecoeur, O.; Lagouarde, J. P.

1989-01-01

NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) Global Vegetation Indices (GVI) were used during the 1986 rainy season (June-September) over Senegal to monitor rainfall. The satellite data were used in conjunction with ground-based measurements so as to derive empirical relationships between rainfall and GVI. The regression obtained was then used to map the total rainfall corresponding to the growing season, yielding good results. Normalized Difference Vegetation Indices (NDVI) derived from High Resolution Picture Transmission (HRPT) data were also compared with actual evapotranspiration (ET) data and proved to be closely correlated with it with a time lapse of 20 days.

Comparison of AVHRR and SMMR data for monitoring vegetation phenology on a continental scale

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Choudhury, B. J.

1989-01-01

AVHRR normalized difference vegetation index (NDVI) data for a one-year period were compared with Scanning Multichannel Microwave Radiometer microwave polarization difference temperature (MPDT) data for the study of vegetation phenology. It is shown that the MPDT response differs considerably from the seasonal NDVI pattern. The results do not support the hypothetical relationship between MPDT and leaf water content. It is found that only vegetation types with a substantial seasonal variation in the areal extent of vegetated cover show strong seasonality in MPDT data.

Land Surface Albedo From EPS/AVHRR : Method For Retrieval and Validation

NASA Astrophysics Data System (ADS)

Jacob, G.

2015-12-01

The scope of Land Surface Analysis Satellite Applications Facility (LSA-SAF) is to increase benefit from EUMETSAT Satellites (MSG and EPS) data by providing added value products for the meteorological and environmental science communities with main applications in the fields of climate modelling, environmental management, natural hazards management, and climate change detection. The MSG/SEVIRI daily albedo product is disseminated operationally by the LSA-SAF processing centre based in Portugal since 2009. This product so-called MDAL covers Europe and Africa includes in the visible, near infrared and shortwave bands at a resolution of 3km at the equator. Recently, an albedo product at 1km so-called ETAL has been built from EPS/AVHRR observations in order to primarily MDAL product outside the MSG disk, while ensuring a global coverage. The methodology is common to MSG and EPS data and relies on the inversion of the BRDF (Bidirectional Reflectance Distribution Function) model of Roujean et al. On a given target, ETAL products exploits the variability of viewing angles whereas MDAL looks at the variations of solar illumination. The comparison of ETAL albedo product against MODIS and MSG/SEVIRI products over the year 2015 is instructive in many ways and shows in general a good agreement between them. The dispersion may be accounted by different factors that will be explained The additional information provided by EPS appears to be particularly beneficial for high latitudes during winter and for snow albedo.

Evaluation of Operational Albedo Algorithms For AVHRR, MODIS and VIIRS: Case Studies in Southern Africa

NASA Astrophysics Data System (ADS)

Privette, J. L.; Schaaf, C. B.; Saleous, N.; Liang, S.

2004-12-01

Shortwave broadband albedo is the fundamental surface variable that partitions solar irradiance into energy available to the land biophysical system and energy reflected back into the atmosphere. Albedo varies with land cover, vegetation phenological stage, surface wetness, solar angle, and atmospheric condition, among other variables. For these reasons, a consistent and normalized albedo time series is needed to accurately model weather, climate and ecological trends. Although an empirically-derived coarse-scale albedo from the 20-year NOAA AVHRR record (Sellers et al., 1996) is available, an operational moderate resolution global product first became available from NASA's MODIS sensor. The validated MODIS product now provides the benchmark upon which to compare albedo generated through 1) reprocessing of the historic AVHRR record and 2) operational processing of data from the future National Polar-Orbiting Environmental Satellite System's (NPOESS) Visible/Infrared Imager Radiometer Suite (VIIRS). Unfortunately, different instrument characteristics (e.g., spectral bands, spatial resolution), processing approaches (e.g., latency requirements, ancillary data availability) and even product definitions (black sky albedo, white sky albedo, actual or blue sky albedo) complicate the development of the desired multi-mission (AVHRR to MODIS to VIIRS) albedo time series -- a so-called Climate Data Record. This presentation will describe the different albedo algorithms used with AVHRR, MODIS and VIIRS, and compare their results against field measurements collected over two semi-arid sites in southern Africa. We also describe the MODIS-derived VIIRS proxy data we developed to predict NPOESS albedo characteristics. We conclude with a strategy to develop a seamless Climate Data Record from 1982- to 2020.

Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics

USGS Publications Warehouse

Ji, Lei; Brown, Jesslyn

2017-01-01

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the

Properties of PSCs and Cirrus Determined from AVHRR Data

NASA Technical Reports Server (NTRS)

Hervig, Mark; Pagan, Kathy; Foschi, Patricia G.

1999-01-01

Polar stratospheric clouds (PSCS) and cirrus have been investigated using thermal emission measurements at 10.8 and 12 micrometers wavelength (channels 4 and 5) from the Advanced Very High Resolution Radiometer (AVHRR). The AVHRR signal was evaluated from a theoretical basis to understand the emission from clear and cloudy skies, and models were developed to simulate the AVHRR signal. Signal simulations revealed that nitric acid PSCs are invisible to AVHRR, while ice PSCs and cirrus are readily detectable. Methods were developed to retrieve cloud optical depths, average temperatures, average effective radii, and ice water paths, from AVHRR channels 4 and 5. Properties of ice PSCs retrieved from AVHRR were compared to values derived from coincident radiosondes and from the Polar Ozone and Aerosol Measurement II instrument, showing good agreement.

Estimating solar radiation using NOAA/AVHRR and ground measurement data

NASA Astrophysics Data System (ADS)

Fallahi, Somayeh; Amanollahi, Jamil; Tzanis, Chris G.; Ramli, Mohammad Firuz

2018-01-01

Solar radiation (SR) data are commonly used in different areas of renewable energy research. Researchers are often compelled to predict SR at ground stations for areas with no proper equipment. The objective of this study was to test the accuracy of the artificial neural network (ANN) and multiple linear regression (MLR) models for estimating monthly average SR over Kurdistan Province, Iran. Input data of the models were two data series with similar longitude, latitude, altitude, and month (number of months) data, but there were differences between the monthly mean temperatures in the first data series obtained from AVHRR sensor of NOAA satellite (DS1) and in the second data series measured at ground stations (DS2). In order to retrieve land surface temperature (LST) from AVHRR sensor, emissivity of the area was considered and for that purpose normalized vegetation difference index (NDVI) calculated from channels 1 and 2 of AVHRR sensor was utilized. The acquired results showed that the ANN model with DS1 data input with R2 = 0.96, RMSE = 1.04, MAE = 1.1 in the training phase and R2 = 0.96, RMSE = 1.06, MAE = 1.15 in the testing phase achieved more satisfactory performance compared with MLR model. It can be concluded that ANN model with remote sensing data has the potential to predict SR in locations with no ground measurement stations.

Comparative Analysis of Daytime Fire Detection Algorithms, Using AVHRR Data for the 1995 Fire Season in Canda: Perspective for MODIS

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Y. J.; Fraser, R. H.; Jin, J.-Z.; Park, W. M.; Lau, William K. M. (Technical Monitor)

2001-01-01

Two fixed-threshold Canada Centre for Remote Sensing and European Space Agency (CCRS and ESA) and three contextual GIGLIO, International Geosphere and Biosphere Project, and Moderate Resolution Imaging Spectroradiometer (GIGLIO, IGBP, and MODIS) algorithms were used for fire detection with Advanced Very High Resolution Radiometer (AVHRR) data acquired over Canada during the 1995 fire season. The CCRS algorithm was developed for the boreal ecosystem, while the other four are for global application. The MODIS algorithm, although developed specifically for use with the MODIS sensor data, was applied to AVHRR in this study for comparative purposes. Fire detection accuracy assessment for the algorithms was based on comparisons with available 1995 burned area ground survey maps covering five Canadian provinces. Overall accuracy estimations in terms of omission (CCRS=46%, ESA=81%, GIGLIO=75%, IGBP=51%, MODIS=81%) and commission (CCRS=0.35%, ESA=0.08%, GIGLIO=0.56%, IGBP=0.75%, MODIS=0.08%) errors over forested areas revealed large differences in performance between the algorithms, with no relevance to type (fixed-threshold or contextual). CCRS performed best in detecting real forest fires, with the least omission error, while ESA and MODIS produced the highest omission error, probably because of their relatively high threshold values designed for global application. The commission error values appear small because the area of pixels falsely identified by each algorithm was expressed as a ratio of the vast unburned forest area. More detailed study shows that most commission errors in all the algorithms were incurred in nonforest agricultural areas, especially on days with very high surface temperatures. The advantage of the high thresholds in ESA and MODIS was that they incurred the least commission errors.

Towards a Remote Sensing Based Assessment of Land Susceptibility to Degradation: Examining Seasonal Variation in Land Use-Land Cover for Modelling Land Degradation in a Semi-Arid Context

NASA Astrophysics Data System (ADS)

Mashame, Gofamodimo; Akinyemi, Felicia

2016-06-01

Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

Recent history of large-scale ecosystem disturbances in North America derived from the AVHRR satellite record.

Treesearch

Christopher Potter; Tan Pang-Ning; Vipin Kumar; Chris Kucharik; Steven Klooster; Vanessa Genovese; Warren Cohen; Sean Healey

2005-01-01

Ecosystem structure and function are strongly affected by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the advanced very high resolution radiometer (AVHRR...

Modeling water and heat balance components of large territory for vegetation season using information from polar-orbital and geostationary meteorological satellites

NASA Astrophysics Data System (ADS)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

2015-04-01

-2013 vegetation seasons. To provide the retrieval of Ts.eff, E, Ta, NDVI, B, and LAI the previously developed technologies of AVHRR data processing have been refined and adapted to the region of interest. The updated linear regression estimators for Ts.eff and Tà have been built using representative training samples compiled for above vegetation seasons. The updated software package has been applied for AVHRR data processing to generate estimates of named values. To verify the accuracy of these estimates the error statistics of Ts.eff and Ta derivation has been investigated for various days of named seasons using comparison with in-situ ground-based measurements. On the base of special technology and Internet resources the remote sensing products Tls, E, NDVI, LAI derived from MODIS data and covering the study area have been extracted from LP DAAC web-site for the same vegetation seasons. The reliability of the MODIS-derived Tls estimates has been confirmed via comparison with analogous and collocated ground-, AVHRR-, and SEVIRI-based ones. The prepared remote sensing dataset has also included the SEVIRI-derived estimates of Tls, E, NDVI, Ta at daylight and night-time and daily estimates of LAI. The Tls estimates has been built utilizing the method and technology developed for the retrieval of Tls and E from 15 minutes time interval SEVIRI data in IR channels 10.8 and 12.0 µm (classified as 100% cloud-free and covering the area of interest) at three successive times without accurate a priori knowledge of E. Comparison of the SEVIRI-based Tls retrievals with independent collocated Tls estimates generated at the Land Surface Analysis Satellite Applications Facility (LSA SAF, Lisbon, Portugal) has given daily- or monthly-averaged values of RMS deviation in the range of 2°C for various dates and months during the mentioned vegetation seasons which is quite acceptable result. The reliability of the SEVIRI-based Tls estimates for the study area has been also confirmed by comparing

Analysis of smoke and cloud impact on seasonal and interannual variations in normalized difference vegetation index in Amazon

NASA Astrophysics Data System (ADS)

Kobayashi, H.; Dye, D. G.

2004-12-01

Normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration (NOAA)/Advanced Very High Resolution Radiometer (AVHRR) is a unique measurement of long-term variations in global vegetation dynamics. The NDVI data have been used for the detection of the seasonal and interannual variations in vegetation. However, as reported in several studies, NDVI decreases with the increase in clouds and/or smoke aerosol contaminated in the pixels. This study assesses the smoke and clouds effect on long-term Global Inventory Modeling and Mapping Studies (GIMMS) and Pathfinder AVHRR Land (PAL) NDVI data in Amazon. This knowledge will help developing the correction method in the tropics in the future. To assess the smoke and cloud effects on GIMMS and PAL, we used another satellite-derived data sets; NDVI derived from SPOT/VEGETATION (VGT) data and Aerosol Index (AI) derived from Total Ozone Mapping Spectrometer (TOMS). Since April 1998, VGT has measured the earth surface globally including in Amazon. The advantage of the VGT is that it has blue channel where the smoke and cloud can be easily detected. By analyzing the VGT NDVI and comparing with the AVHRR-based NDVI, we inferred smoke and cloud effect on the AVHRR-based NDVI. From the results of the VGT analysis, we found the large NDVI seasonality in South and Southeastern Amazon. In these areas, the NDVI gradually increased from April to July and decreased from August to October. However the sufficient NDVI data were not existed from August to November when the smoke and cloud pixels were masked using blue reflectance. Thus it is said that the smoke and clouds mainly cause the large decreases in NDVI between August and November and NDVI has little vegetation signature in these months. Also we examined the interannual variations in NDVI and smoke aerosol. Then the decrease in NDVI is well consistent with the increase in the increase in AI. Our results suggest that the months between April

Reconstructed high-resolution scatterometer data: a comparison with AVHRR vegetation index images for regional-scale monitoring of tropical rain forests

NASA Astrophysics Data System (ADS)

Hardin, Perry J.; Long, David G.

1993-08-01

There is considerable interest in utilizing microwave and visible spectrum imagery for the assessment of tropical rain forests. Because rain forest spans large sub-continental areas, medium resolution (1 - 16 km) imagery will play an important role in providing a global perspective of any forest removal or change. Since 1978, AVHRR imagery from NOAA polar orbiters has provided coverage of tropical regions at this desirable resolution, but much of the imagery is plagued with heavy cloud cover typical of equatorial regions. In contrast, no historical source of active microwave imagery at native 1 - 16 km resolution exists for all the global rain forest regions. In this paper, the authors compare the utility of Seasat scatterometer (SASS) ku-band microwave data to early-date AVHRR vegetation index products for discrimination of tropical vegetation formations. When considered separately, both the AVHRR imagery and the SASS imagery could be used to distinguish between broad categories of equatorial land cover, but the AVHRR imagery was slightly superior. When combined, the two data sets provided discrimination capability superior than could be obtained by using either set alone.

A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series

NASA Technical Reports Server (NTRS)

Pinzon, Jorge E.; Tucker, Compton J.

2014-01-01

The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.

Capability of AVHRR data in discriminating rangeland cover mixtures

USGS Publications Warehouse

Senay, Gabriel B.; Elliott, R.L.

2002-01-01

A combination of high temporal resolution Advanced Very High Resolution Radiometer (AVHRR) data and high spatial information Map Information Analysis and Display System (MIADS) landuse/landcover data from the United States Department of Agriculture-Natural Resources Conservation Service (USDA-NRCS) were used to investigate the feasibility of using the combined dataset for regional evapotranspiration (ET) studies. It was shown that the biweekly maximum Normalized Difference Vegetation Index (NDVI) composite AVHRR data were capable of discriminating rangelands with different types of trees and shrubs species. AVHRR data also showed a potential to distinguish canopy cover differences within a mix of similar species. The combination of MIADS data and AVHRR data can be used to study temporal dynamics of various cover types for use in regional ET estimates.

Seasonal and Non-seasonal Sea Level Variations by Exchange of Water with Land Hydrology

NASA Technical Reports Server (NTRS)

Chao, Benjamin F.; Au, A. Y.

2004-01-01

The global ocean exchanges a large amount of water, seasonally or non-seasonally, with land hydrology. Apart from the long-term melting of ice sheets and glaciers, the water is exchanged directly as land runoff R, and indirectly via atmosphere in the form of precipitation minus evapo-transpiration P-E. On land, the hydrological budget balance is soil moisture S = P-E-R. The runoff R has been difficult to monitor; but now by combining the following two data sets one can obtain a global estimate, subject to the spatial and temporal resolutions afforded by the data: (1) The space gravity mission GRACE yields monthly S estimate on a spatial scale larger than approx. 1000 km over the last 2.5 years; (2) The atmospheric circulation model output, such as from NCEP, provides proxy estimates for P-E at monthly and approx. 200 km resolutions. We will discuss these estimates and the effects on the global ocean water budget and hence sea level.

Analysis of urban regions using AVHRR thermal infrared data

USGS Publications Warehouse

Wright, Bruce

1993-01-01

Using 1-km AVHRR satellite data, relative temperature difference caused by conductivity and inertia were used to distinguish urban and non urban land covers. AVHRR data that were composited on a biweekly basis and distributed by the EROS Data Center in Sioux Falls, South Dakota, were used for the classification process. These composited images are based on the maximum normalized different vegetation index (NDVI) of each pixel during the 2-week period using channels 1 and 2. The resultant images are nearly cloud-free and reduce the need for extensive reclassification processing. Because of the physiographic differences between the Eastern and Western United States, the initial study was limited to the eastern half of the United States. In the East, the time of maximum difference between the urban surfaces and the vegetated non urban areas is the peak greenness period in late summer. A composite image of the Eastern United States for the 2-weel time period from August 30-Septmeber 16, 1991, was used for the extraction of the urban areas. Two channels of thermal data (channels 3 and 4) normalized for regional temperature differences and a composited NDVI image were classified using conventional image processing techniques. The results compare favorably with other large-scale urban area delineations.

Midwest agriculture and ENSO: A comparison of AVHRR NDVI3g data and crop yields in the United States Corn Belt from 1982 to 2014

NASA Astrophysics Data System (ADS)

Glennie, Erin; Anyamba, Assaf

2018-06-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) data were compared to National Agricultural Statistics Service (NASS) corn yield data in the United States Corn Belt from 1982 to 2014. The main objectives of the comparison were to assess 1) the consistency of regional Corn Belt responses to El Niño/Southern Oscillation (ENSO) teleconnection signals, and 2) the reliability of using NDVI as an indicator of crop yield. Regional NDVI values were used to model a seasonal curve and to define the growing season - May to October. Seasonal conditions in each county were represented by NDVI and land surface temperature (LST) composites, and corn yield was represented by average annual bushels produced per acre. Correlation analysis between the NDVI, LST, corn yield, and equatorial Pacific sea surface temperature anomalies revealed patterns in land surface dynamics and corn yield, as well as typical impacts of ENSO episodes. It was observed from the study that growing seasons coincident with La Niña events were consistently warmer, but El Niño events did not consistently impact NDVI, temperature, or corn yield data. Moreover, the El Niño and La Niña composite images suggest that impacts vary spatially across the Corn Belt. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be attributed to soy crops and other background interference. The overall correlation between the total growing season NDVI anomaly and detrended corn yield was 0.61(p = 0.00013), though the strength of the relationship varies across the Corn Belt.

Using satellite data on meteorological and vegetation characteristics and soil surface humidity in the Land Surface Model for the vast territory of agricultural destination

NASA Astrophysics Data System (ADS)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Vasilenko, Eugene; Volkova, Elena; Kukharsky, Alexander

2017-04-01

The model of water and heat exchange between vegetation covered territory and atmosphere (LSM, Land Surface Model) for vegetation season has been developed to calculate soil water content, evapotranspiration, infiltration of water into the soil, vertical latent and sensible heat fluxes and other water and heat balances components as well as soil surface and vegetation cover temperatures and depth distributions of moisture and temperature. The LSM is suited for utilizing satellite-derived estimates of precipitation, land surface temperature and vegetation characteristics and soil surface humidity for each pixel. Vegetation and meteorological characteristics being the model parameters and input variables, correspondingly, have been estimated by ground observations and thematic processing measurement data of scanning radiometers AVHRR/NOAA, SEVIRI/Meteosat-9, -10 (MSG-2, -3) and MSU-MR/Meteor-M № 2. Values of soil surface humidity has been calculated from remote sensing data of scatterometers ASCAT/MetOp-A, -B. The case study has been carried out for the territory of part of the agricultural Central Black Earth Region of European Russia with area of 227300 km2 located in the forest-steppe zone for years 2012-2015 vegetation seasons. The main objectives of the study have been: - to built estimates of precipitation, land surface temperatures (LST) and vegetation characteristics from MSU-MR measurement data using the refined technologies (including algorithms and programs) of thematic processing satellite information matured on AVHRR and SEVIRI data. All technologies have been adapted to the area of interest; - to investigate the possibility of utilizing satellite-derived estimates of values above in the LSM including verification of obtained estimates and development of procedure of their inputting into the model. From the AVHRR data there have been built the estimates of precipitation, three types of LST: land skin temperature Tsg, air temperature at a level of

Advanced Very High Resolution Radiometer - AVHRR - NOAA Satellite

Science.gov Websites

Information System (NOAASIS); Office of Satellite and Product Operations » DOC » NOAA  » NESDIS » NOAASIS NOAA Satellite Information System Advanced Very High Resolution Radiometer - AVHRR The ) or the USGS AVHRR site. Satellite Products and Services Division Direct Services Branch Phone: 301

AVHRR-based drought-observing system for monitoring the environment and socioeconomic activities

NASA Astrophysics Data System (ADS)

Kogan, F.

From all natural disaster, drought is the least understandable and the most damaging environmental phenomenon. Although in pre-satellite era, climate data were used for drought monitoring, drought specifics created problems in early drought detection start/end, monitoring its expansion/contraction, intensity and area coverage and the most important, timely estimation of the impacts on the environment and socioeconomic activities. The latest prevented to take prompt measures in mitigating negative consequences of drought for the society. Advances in remote sensing of the past ten years, contributed to the development of comprehensive drought monitoring system and numerous applications, which helped to make decisions for monitoring the environment and predicting sustainable socioeconomic activities. This paper discusses satellite-based land-surface observing system, which provides wells of information used for monitoring such unusual natural disaster as drought. This system was developed from the observations of the Advanced Very High Resolution Radiometer (AVHRR) flown on NOAA operational polar-orbiting satellites. The AVHRR data were packed into the Global Vegetation Index (GVI) product, which have served the global community since 1981. The GVI provided reflectances and indices (4 km spacial resolution) every seven days for each 16 km map cell between 75EN and 55ES covering all land ecosystems. The data includes raw and calibrated radiances in the visible, near infrared and infrared spectral bands, processed (with eliminated high frequency noise) radiances, normalized difference vegetation index (NDVI), 20-year climatology, vegetation condition indices and also products, such as vegetation health, drought, vegetation fraction, fire risk etc. In the past ten years, users around the world used this information addressing different issues of drought impacts on socioeconomic activities and responded positively to real time drought information place regularly on the

Seasonal vegetation characteristics of the United States

USGS Publications Warehouse

Reed, Bradley C.; Yang, Limin

1997-01-01

The U.S. Geological Survey's EROS Data Center has created a prototype 1‐km resolution data base of vegetation seasonal characteristics. The characteristics are derived from time‐series NDVI data collected by the AVHRR satellite sensor. Information covering the 5 years 1989–1993 is included in the data base. Although quantitative validation of the seasonal characteristics cannot be made until several evaluation efforts are completed, general observations are possible by viewing images of the seasonal parameters. Figures 2 through 8 show several examples of the seasonal characteristics data base.

Monitoring arid lands using AVHRR-observed visible reflectance and SMMR37-GHz polarization difference

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1990-01-01

Visible reflectance along a transect through the Sahel and Sudan zones of Africa has been derived from observations by the AVHRR on the NOAA-7 and NOAA-9 satellites and compared with concurrent observations of the 37-GHz polarization difference by the SMMR on the Nimbus-7 satellite. The study period was January 1982 to December 1986, which included an unprecedented drought during 1984 over the Sahel zone. While spatial and temporal patterns of these two data sets are found to be highly correlated, there are also quantitative differences which need to be understood.

Modeling seasonal and interannual variability in ecosystem carbon cycling for the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Potter, Christopher; Klooster, Steven; de Carvalho, Claudio Reis; Genovese, Vanessa Brooks; Torregrosa, Alicia; Dungan, Jennifer; Bobo, Matthew; Coughlan, Joseph

2001-05-01

Previous field measurements have implied that undisturbed Amazon forests may represent a substantial terrestrial sink for atmospheric carbon dioxide. We investigated this hypothesis using a regional ecosystem model for net primary production (NPP) and soil biogeochemical cycling. Seasonal and interannual controls on net ecosystem production (NEP) were studied with integration of high-resolution (8-km) multiyear satellite data to characterize Amazon land surface properties over time. Background analysis of temporal and spatial relationships between regional rainfall patterns and satellite observations (for vegetation land cover, fire counts, and smoke aerosol effects) reveals several notable patterns in the model driver data. Autocorrelation analysis for monthly vegetation "greenness" index (normalized difference vegetation index, NDVI) from the advanced very high resolution radiometer (AVHRR) and monthly rainfall indicates a significant lag time correlation of up to 12 months. At lag times approaching 36 months, autocorrelation function (ACF) values did not exceed the 95% confidence interval at locations west of about 47°W, which is near the transition zone of seasonal tropical forest and other (nonforest) vegetation types. Even at lag times of 12 months or less, the location near Manaus (approximately 60°W) represents the farthest western point in the Amazon region where seasonality of rainfall accounts significantly for monthly variations in forest phenology, as observed using NDVI. Comparisons of NDVI seasonal profiles in areas of the eastern Amazon widely affected by fires (as observed from satellite) suggest that our adjusted AVHRR-NDVI captures year-to-year variation in land cover greenness with minimal interference from small fires and smoke aerosols. Ecosystem model results using this newly generated combination of regional forcing data from satellite suggest that undisturbed Amazon forests can be strong net sinks for atmospheric carbon dioxide

[Dendrolimus spp. damage monitoring by using NOAA/AVHRR data].

PubMed

Zhang, Yushu; Ban, Xianxiu; Chen, Pengshi; Feng, Rui; Ji, Ruipeng; Xiao, Yan

2005-05-01

This paper approached the feasibility of quantitatively monitoring Dendrolimus spp. damage by using NOAA/ AVHRR data. The damaged rate of needle leaf was used to represent Dendrolimus spp. harming degree, and < 30%, 30%-60% and > 60% of damaged rate was defined as low, medium and severe harming degree, respectively. The correlation equation of damaged rate and normalized vegetation index (NDVI) was established, based on the ground spectrum observation. The NDVI was 0.8823 when no damage occurred. A relative NDVI value of damaged to undamaged area was used to express the remote sensing index of low, medium and severe harming degree. The index was 1 for undamaged forest, and 0.78-1, 0.57-0.78 and < 0.57 for low, medium and severe harming degrees, respectively. The mixed pixels were separated by linear addable vertical vegetation index in the monitoring, and the quantitative monitoring and analysis was accomplished for years when the three damage degrees happened. It was shown that AVHRR data could be more available in quantitatively monitoring and analyzing serious damage, while low degree damage was difficult to distinguish by AVHRR data, due to the differences of surface properties and atmospheric influences, as well as the lower space resolution of NOAA/AVHRR. The damaged area estimated by AVHRR was 12.1%-14.3% lower than that by TM.

Effect of land use on the seasonal variation of streamwater quality in the Wei River basin, China

NASA Astrophysics Data System (ADS)

Yu, S.; Xu, Z.; Wu, W.; Zuo, D.

2015-05-01

The temporal effect of land use on streamwater quality needs to be addressed for a better understanding of the complex relationship between land use and streamwater quality. In this study, GIS and Pearson correlation analysis were used to determine whether there were correlations of land-use types with streamwater quality at the sub-basin scale in the Wei River basin, China, during dry and rainy seasons in 2012. Temporal variation of these relations was observed, indicating that relationships between water quality variables and proportions of different land uses were weaker in the rainy season than that in the dry season. Comparing with other land uses, agriculture and urban lands had a stronger relationship with water quality variables in both the rainy and dry seasons. These results suggest that the aspect of temporal effects should be taken into account for better land-use management.

Utilization of satellite remote sensing data on land surface characteristics in water and heat balance component modeling for vegetation covered territories

NASA Astrophysics Data System (ADS)

Muzylev, Eugene; Uspensky, Alexander; Startseva, Zoya; Volkova, Elena; Kukharsky, Alexander; Uspensky, Sergey

2010-05-01

The model of vertical water and heat transfer in the "soil-vegetation-atmosphere" system (SVAT) for vegetation covered territory has been developed, allowing assimilating satellite remote sensing data on land surface condition as well as accounting for heterogeneities of vegetation and meteorological characteristics. The model provides the calculation of water and heat balance components (such as evapotranspiration Ev, soil water content W, sensible and latent heat fluxes and others ) as well as vertical soil moisture and temperature distributions, temperatures of soil surface and foliage, land surface brightness temperature for any time interval within vegetation season. To describe the landscape diversity soil constants and leaf area index LAI, vegetation cover fraction B, and other vegetation characteristics are used. All these values are considered to be the model parameters. Territory of Kursk region with square about 15 thousands km2 situated in the Black Earth zone of Central Russia was chosen for investigation. Satellite-derived estimates of land surface characteristics have been constructed under cloud-free condition basing AVHRR/NOAA, MODIS/EOS Terra and EOS Aqua, SEVIRI/Meteosat-8, -9 data. The developed technologies of AVHRR data thematic processing have been refined providing the retrieval of surface skin brightness temperature Tsg, air foliage temperature Ta, efficient surface temperature Ts.eff and emissivity E, as well as derivation of vegetation index NDVI, B, and LAI. The linear regression estimators for Tsg, Ta and LAI have been built using representative training samples for 2003-2009 vegetation seasons. The updated software package has been applied for AVHRR data thematic processing to generate named remote sensing products for various dates of the above vegetation seasons. The error statistics of Ta, Ts.eff and Тsg derivation has been investigated for various samples using comparison with in-situ measurements that has given RMS errors in the

Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

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

Kasischke, E.S.; French, N.H.F.; Harrell, P.

1993-06-01

Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5% of all fires with sizes greater than 2,000ha with no falsemore » alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61% of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used.« less

Monitoring of wildfires in boreal forests using large area AVHRR NDVI composite image data

NASA Technical Reports Server (NTRS)

Kasischke, Eric S.; French, Nancy H. F.; Harrell, Peter; Christensen, Norman L., Jr.; Ustin, Susan L.; Barry, Donald

1993-01-01

Normalized difference vegetation index (NDVI) composite image data, produced from AVHRR data collected in 1990, were evaluated for locating and mapping the areal extent of wildfires in the boreal forests of Alaska during that year. A technique was developed to map forest fire boundaries by subtracting a late-summer AVHRR NDVI image from an early summer scene. The locations and boundaries of wildfires within the interior region of Alaska were obtained from the Alaska Fire Service, and compared to the AVHRR-derived fire-boundary map. It was found that AVHRR detected 89.5 percent of all fires with sizes greater than 2000 ha with no false alarms and that, for most cases, the general shape of the fire boundary detected by AVHRR matched those mapped by field observers. However, the total area contained within the fire boundaries mapped by AVHRR were only 61 percent of those mapped by the field observers. However, the AVHRR data used in this study did not span the entire time period during which fires occurred, and it is believed the areal estimates could be improved significantly if an expanded AVHRR data set were used.

AVHRR imagery reveals Antarctic ice dynamics

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Vornberger, Patricia L.

1990-01-01

A portion of AVHRR data taken on December 5, 1987 at 06:15 GMT over a part of Antarctica is used here to show that many of the most significant dynamic features of ice sheets can be identified by a careful examination of AVHRR imagery. The relatively low resolution of this instrument makes it ideal for obtaining a broad view of the ice sheets, while its wide swath allows coverage of areas beyond the reach of high-resolution imagers either currently in orbit or planned. An interpretation is given of the present data, which cover the area of ice streams that drain the interior of the West Antarctic ice sheet into the Ross Ice Shelf.

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

PubMed

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

2009-10-01

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

Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS

NASA Technical Reports Server (NTRS)

Morisette, Jeffrey T.; Pinzon, Jorge E.; Brown, Molly E.; Tucker, Jim; Justice, Christopher O.

2004-01-01

The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.

Arctic sea ice albedo from AVHRR

NASA Technical Reports Server (NTRS)

Lindsay, R. W.; Rothrock, D. A.

1994-01-01

The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably. The poor calibration of AVHRR channels 1 and 2 is another large impediment to making accurate albedo estimates.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

An analysis of IGBP global land-cover characterization process

USGS Publications Warehouse

Loveland, Thomas R.; Zhu, Zhiliang; Ohlen, Donald O.; Brown, Jesslyn F.; Reed, Bradley C.; Yang, Limin

1999-01-01

The international Geosphere Biosphere Programme (IGBP) has called for the development of improved global land-cover data for use in increasingly sophisticated global environmental models. To meet this need, the staff of the U.S. Geological Survey and the University of Nebraska-Lincoln developed and applied a global land-cover characterization methodology using 1992-1993 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) and other spatial data. The methodology, based on unsupervised classification with extensive postclassification refinement, yielded a multi-layer database consisting of eight land-cover data sets, descriptive attributes, and source data. An independent IGBP accuracy assessment reports a global accuracy of 73.5 percent, and continental results vary from 63 percent to 83 percent. Although data quality, methodology, interpreter performance, and logistics affected the results, significant problems were associated with the relationship between AVHRR data and fine-scale, spectrally similar land-cover patterns in complex natural or disturbed landscapes.

Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2005-01-01

Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

Regional Features and Seasonality of Land-Atmosphere Coupling over Eastern China

NASA Astrophysics Data System (ADS)

Gao, Chujie; Chen, Haishan; Sun, Shanlei; Xu, Bei; Ongoma, Victor; Zhu, Siguang; Ma, Hedi; Li, Xing

2018-06-01

Land-atmosphere coupling is a key process of the climate system, and various coupling mechanisms have been proposed before based on observational and numerical analyses. The impact of soil moisture (SM) on evapotranspiration (ET) and further surface temperature (ST) is an important aspect of such coupling. Using ERA-Interim data and CLM4.0 offline simulation results, this study further explores the relationships between SM/ST and ET to better understand the complex nature of the land-atmosphere coupling (i.e., spatial and seasonal variations) in eastern China, a typical monsoon area. It is found that two diagnostics of land-atmosphere coupling (i.e., SM-ET correlation and ST-ET correlation) are highly dependent on the climatology of SM and ST. By combining the SM-ET and ST-ET relationships, two "hot spots" of land-atmosphere coupling over eastern China are identified: Southwest China and North China. In Southwest China, ST is relatively high throughout the year, but SM is lowest in spring, resulting in a strong coupling in spring. However, in North China, SM is relatively low throughout the year, but ST is highest in summer, which leads to the strongest coupling in summer. Our results emphasize the dependence of land-atmosphere coupling on the seasonal evolution of climatic conditions and have implications for future studies related to land surface feedbacks.

Temporal and spatial change in coastal ecosystems using remote sensing: Example with Florida Bay, USA, emphasizing AVHRR imagery

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

Stumpf, R.P.; Frayer, M.L.

1997-06-01

Florida Bay, at the southern tip of Florida, USA, has undergone dramatic changes in recent years. Following seagrass dieoffs starting in the late 1980`s, both algal blooms and high turbidity (the latter from resuspended sediments) have been reported as more common in the Bay. Remotely sensed data, particularly from the AVHRR (advanced very high resolution radiometer), can provide information on conditions prior to the start of monitoring programs as well as provide additional spatial detail on water clarity and particulate loads in this estuary . The AVHRR record currently available to us consists of over 600 usable scenes from December,more » 1989. Comparisons with field data have provided relationships with light attenuation, total suspended solids, and other turbidity measures. The imagery shows the seasonal change in turbidity resulting from high winds associated with winter cold fronts. Over the seven-year record, areas of clear water have decreased in the north-central Bay, while expanding in the southwestern Bay.« less

Links between land use change and recent dry season droughts in Amazonia

NASA Astrophysics Data System (ADS)

Khanna, J.; Medvigy, D.

2012-12-01

The Amazon region experienced catastrophic and unusually severe droughts in 2005 and 2010. These two droughts were phenomenologically different from the other, more common, El Niño-related droughts. Whereas El Niño-related droughts mostly affect the eastern and south-eastern parts of the region during the wet season (December-March), the droughts of 2005 and 2010 were most severe during the dry season (June-August) and affected the southern and western parts of the Amazon. A global warming driven mechanism has been suggested for these droughts wherein decreased moisture transport into the basin during the dry season is caused by anomalously high tropical north Atlantic SSTs, which weaken the northern hemisphere Hadley cell. But the facts that dry season droughts have been historically rare in this region and that the 2005 and 2010 droughts were strongest around locations of recent land use change activity suggest that deforestation may be contributing to this inter-annual variability in precipitation. This study addresses this research question by numerically modeling the 2005 and 2010 drought events for two land use scenarios, one of which (Deforested or DEF) represents the current state of land use in the Amazon and the other (Pristine Forest or PRF) represents a scenario of no deforestation. A variable resolution GCM, the Ocean-Land-Atmosphere Model (OLAM), is used to model these events. Land surface processes and soil moisture during the drought period are simulated using the Land Ecosystem Atmosphere Feedback model. The state of land cover in the Amazon in the two drought years is obtained from satellite-based land cover maps. The land grid has a variable resolution ranging from ≈75km in the South American sector to ≈200km elsewhere. This variable-resolution approach helps resolve topographic features and the medium-to-large scale land use patches in the Amazon area. The atmospheric runs are forced by National Oceanic and Atmospheric Administration

Evapotranspiration from combined reflected solar and emitted terrestrial radiation - Preliminary FIFE results from AVHRR data

NASA Technical Reports Server (NTRS)

Goward, S. N.; Hope, A. S.

1989-01-01

The relation between remotely sensed spectral vegetation indices and thermal IR measurements is studied. Land surface evapotranspiration is evaluated based on this relationship. Analysis of the AVHRR data, obtained in Kansas in 1987, reveal a strong correlation between the spectral vegetation indices and surface temperature and this relation covaries with surface moisture conditions. It is noted that the relation between remotely sensed measurements of canopy green foliage and surface temperature is useful for examining variations in the interface thermal inertia and energy balance Bowen ratio.

Operational atmospheric correction of AVHRR visible and infrared data

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

Vermote, E.; El Saleous, N.; Roger, J.C.

1995-12-31

The satellite level radiance is affected by the presence of the atmosphere between the sensor and the target. The ozone and water vapor absorption bands affect the signal recorded by the AVHRR visible and near infrared channels respectively. The Rayleigh scattering mainly affects the visible channel and is more pronounced when dealing with small sun elevations and large view angles. The aerosol scattering affects both channels and is certainly the most challenging term for atmospheric correction because of the spatial and temporal variability of both the type and amount of particles in the atmosphere. This paper presents the equation ofmore » the satellite signal, the scheme to retrieve atmospheric properties and corrections applied to AVHRR observations. The operational process uses TOMS data and a digital elevation model to correct for ozone absorption and rayleigh scattering. The water vapor content is evaluated using the split-window technique that is validated over ocean using 1988 SSM/I data. The aerosol amount retrieval over Ocean is achieved in channels 1 and 2 and compared to sun photometer observations to check consistency of the radiative transfer model and the sensor calibration. Over land, the method developed uses reflectance at 3.75 microns to deduce target reflectance in channel 1 and retrieve aerosol optical thickness that can be extrapolated in channel 2. The method to invert the reflectance at 3.75 microns is based on MODTRAN simulations and is validated by comparison to measurements performed during FIFE 87. Finally, aerosol optical thickness retrieved over Brazil and Eastern US is compared to sun photometer measurements.« less

Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition. [Advanced Very High Resolution Radiometer

NASA Technical Reports Server (NTRS)

Ormsby, J. P.

1982-01-01

An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

Comparison of North and South American biomes from AVHRR observations

NASA Technical Reports Server (NTRS)

Goward, Samuel N.; Dye, Dennis; Kerber, Arlene; Kalb, Virginia

1987-01-01

Previous analysis of the North American continent with AVHRR-derived vegetation index measurements showed a strong relation between known patterns of vegetation seasonality, productivity and the spectral vegetation index measurements. This study extends that analysis to South America to evaluate the degree to which these findings extend to tropical regions. The results show that the spectral vegetation index measurements provide a general indicator of vegetation activity across the major biomes of the Western Hemisphere of the earth, including tropical regions. The satellite-observed patterns are strongly related to the known climatology of the continents and may offer a means to improve understanding of global bioclimatology. For example, South America is shown to have a longer growing season with much earlier spring green-up than North America. The time integral of the measurements, computed from 12 composited monthly values, produces a value that is related to published net primary productivity data. However, limited net primary production data does not allow complete evaluation of satellite-observed contrasts between North and South American biomes. These results suggest that satellite-derived spectral vegetation index measurements are of great potential value in improving knowledge of the earth's biosphere.

Establishment of warm-season native grasses and forbs on drastically disturbed lands

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

Miller, S.

Establishment of warm-season native grasses and forbs (WSNGs) has been viewed by landowners, agronomists, natural resource managers and reclamation specialists as being too expensive and difficult, especially for reclamation, which requires early stand closure and erosion control. Natural resource managers have learned a great deal about establishing WSNGs since the implementation of the 1985 Farm Bill`s Conservation Reserve Program (CRP). Reclamation specialists must begin to use this information to improve reclamation success. Quality control of seed equipment and planting methods has been proven to be the crucial first step in successful establishment. Seedling germination, growth and development of WSNGs aremore » different from that of introduced cool-season grasses and legumes. Specialized seed drills and spring planting periods are essential. Because shoot growth lags far behind root growth the first two seasons, WSNGs often are rejected for reclamation use. Usually, the rejection is based on preconceived notions that bare ground will erode and on reclamation specialists` desire for a closed, uniform, grassy lawn. WSNG`s extensive root systems inhibit rill and gully erosion by the fall of the first season. Planting a weakly competitive, short-lived nurse crop such as perennial ryegrass (Lolium perenne) at low rates with the WSNG mixture can reduce first-season sheet and rill erosion problems and give an appearance of a closed stand. Benefits of WSNGs in soil building and their acid-tolerance make them ideal species for reclamation of drastically disturbed lands. WSNGs and forbs enhance wildlife habitat and promote natural succession and the invasion of the reclamation site by other native species, particularly hardwood trees, increasing diversity and integrating the site into the local ecosystem. This is perhaps their most important attribute. Most alien grasses and legumes inhibit natural succession, slowing the development of a stable mine soil ecosystem

Cross comparison of the Collection 6 and Collection 6.1 Terra and Aqua MODIS Bands 1 and 2 using AVHRR N15 and N19

NASA Astrophysics Data System (ADS)

Chen, Xuexia; Wu, Aisheng; Xiong, Xiaoxiong J.; Chen, Na

2017-09-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key scientific instrument that was launched into Earth orbit by NASA in 1999 on board the Terra (EOS AM) satellite and in 2002 on board the Aqua (EOS PM) satellite. Terra and Aqua MODIS collect the entire Earth's images every 1 to 2 days in 36 spectral bands. MODIS band 1 (0.620- 0.670 μm) and band 2 (0.841-0.876 μm) have nadir spatial resolution of 250 m and their measurements are crucial to derive key land surface products. This study evaluates the performance of the Collection 6 (C6, and C6.1) L1B of both Terra and Aqua MODIS bands 1 and 2 using Simultaneous Nadir Overpass (SNO) data to compare with AVHRR/3 sensors. We examine the relative stability between Terra and Aqua MODIS in reference to NOAA N15 and N19 the Advanced Very High Resolution Radiometer (AVHRR/3). The comparisons for MODIS to AVHRR/3 are over a fifteenyear period from 2002 to 2017. Results from this study provide a quantitative assessment of Terra and Aqua MODIS band 1 and band 2 calibration stability and the relative differences through the NOAA N15 and N19 AVHRR/3 sensors.

AVHRR for monitoring global tropical deforestation

NASA Technical Reports Server (NTRS)

Malingreau, J. P.; Laporte, N.; Tucker, C. J.

1989-01-01

Advanced Very High Resolution Radiometer (AVHRR) data have been used to assess the dynamics of forest trnsformations in three parts of the tropical belt. A large portion of the Amazon Basin has been systematically covered by Local Area Coverage (LAC) data in the 1985-1987 period. The analysis of the vegetation index and thermal data led to the identification and measurement of large areas of active deforestation. The Kalimantan/Borneo forest fires were monitored and their impact was evaluated using the Global Area Coverage (GAC) 4 km resolution data. Finally, High Resolution Picture Transmission (HRPT) data have provided preliminary information on current activities taking place at the boundary between the savanna and the forest in the Southern part of West Africa. The AVHRR approach is found to be a highly valuable means for carrying out deforestation assessments in regional and global perspectives.

Agreement evaluation of AVHRR and MODIS 16-day composite NDVI data sets

USGS Publications Warehouse

Ji, Lei; Gallo, Kevin P.; Eidenshink, Jeffery C.; Dwyer, John L.

2008-01-01

Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended.

The Calibration of AVHRR Visible Dual Gain using Meteosat-8 for NOAA-16 to 18

NASA Technical Reports Server (NTRS)

Doelling, David R.; Garber, Donald P.; Avey, L. A.; Nguyen, Louis; Minnis, Patrick

2007-01-01

The NOAA AVHRR program has given the remote sensing community over 25 years of imager radiances to retrieve global cloud, vegetation, and aerosol properties. This dataset can be used for long-term climate research, if the AVHRR instrument is well calibrated. Unfortunately, the AVHRR instrument does not have onboard visible calibration and does degrade over time. Vicarious post-launch calibration is necessary to obtain cloud properties that are not biased over time. The recent AVHRR-3 instrument has a dual gain in the visible channels in order to achieve greater radiance resolution in the clear-sky. This has made vicarious calibration of the AVHRR-3 more difficult to unravel. Reference satellite radiances from well-calibrated instruments, usually equipped with solar diffusers, such as MODIS, have been used to successfully vicariously calibrate other visible instruments. Transfer of calibration from one satellite to another using co-angled, collocated, coincident radiances has been well validated. Terra or Aqua MODIS and AVHRR comparisons can only be performed over the poles during summer. However, geostationary satellites offer a transfer medium that captures both parts of the dual gain. This AVHRR-3 calibration strategy uses, calibrated with MODIS, Meteosat-8 radiances simultaneously to determine the dual gains using 50km regions. The dual gain coefficients will be compared with the nominal coefficients. Results will be shown for all visible channels for NOAA-17.

The analysis of polar clouds from AVHRR satellite data using pattern recognition techniques

NASA Technical Reports Server (NTRS)

Smith, William L.; Ebert, Elizabeth

1990-01-01

The cloud cover in a set of summertime and wintertime AVHRR data from the Arctic and Antarctic regions was analyzed using a pattern recognition algorithm. The data were collected by the NOAA-7 satellite on 6 to 13 Jan. and 1 to 7 Jul. 1984 between 60 deg and 90 deg north and south latitude in 5 spectral channels, at the Global Area Coverage (GAC) resolution of approximately 4 km. This data embodied a Polar Cloud Pilot Data Set which was analyzed by a number of research groups as part of a polar cloud algorithm intercomparison study. This study was intended to determine whether the additional information contained in the AVHRR channels (beyond the standard visible and infrared bands on geostationary satellites) could be effectively utilized in cloud algorithms to resolve some of the cloud detection problems caused by low visible and thermal contrasts in the polar regions. The analysis described makes use of a pattern recognition algorithm which estimates the surface and cloud classification, cloud fraction, and surface and cloudy visible (channel 1) albedo and infrared (channel 4) brightness temperatures on a 2.5 x 2.5 deg latitude-longitude grid. In each grid box several spectral and textural features were computed from the calibrated pixel values in the multispectral imagery, then used to classify the region into one of eighteen surface and/or cloud types using the maximum likelihood decision rule. A slightly different version of the algorithm was used for each season and hemisphere because of differences in categories and because of the lack of visible imagery during winter. The classification of the scene is used to specify the optimal AVHRR channel for separating clear and cloudy pixels using a hybrid histogram-spatial coherence method. This method estimates values for cloud fraction, clear and cloudy albedos and brightness temperatures in each grid box. The choice of a class-dependent AVHRR channel allows for better separation of clear and cloudy pixels than

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

1991-01-01

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement, and Transition to MODIS

NASA Technical Reports Server (NTRS)

Fowler, Charles; Maslanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

2001-01-01

The AVHRR-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and a cloud mask composited into twice- per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 deg. latitude. Our goals under this grant, in general, are four-fold: 1. To quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements. 2. To determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output. 3. To investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program. 4. To compare an annual cycle of the AVHRR Pathfinder products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period. Year One tasks include intercomparisons of the Pathfinder products with field measurements, testing of algorithm assumptions, collection of field data, and further validation and possible improvement of the multi-sensor ice motion fields. Achievements for these tasks are summarized below.

The effect of water vapour on the normalized difference vegetation index derived for the Sahelian region from NOAA AVHRR data

NASA Technical Reports Server (NTRS)

Justice, Christopher O.; Eck, T. F.; Tanre, Didier; Holben, B. N.

1991-01-01

The near-infrared channel of the NOAA advanced very high resolution radiometer (AVHRR) contains a water vapor absorption band that affects the determination of the normalized difference vegetation index (NDVI). Daily and seasonal variations in atmospheric water vapor within the Sahel are shown to affect the use of the NDVI for the estimation of primary production. This water vapor effect is quantified for the Sahel by radiative transfer modeling and empirically using observations made in Mali in 1986.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm

Treesearch

Kathleen M. Bergen; Daniel G. Brown; James F. Rutherford; Eric J. Gustafson

2005-01-01

A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our...

Estimation of carbon emissions from wildfires in Alaskan boreal forests using AVHRR data

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

Kasischke, E.S.; French, N.H.F.; Bourgeau-Chavez, L.L

1993-06-01

The objectives of this research study were to evaluate the utility of using AVHRR data for locating and measuring the areal extent of wildfires in the boreal forests of Alaska and to estimate the amount of carbon being released during these fires. Techniques were developed to using the normalized difference vegetation signature derived from AVHRR data to detect and measure the area of fires in Alaska. A model was developed to estimate the amount of biomass/carbon being stored in Alaskan boreal forests, and the amount of carbon released during fires. The AVHRR analysis resulted in detection of > 83% ofmore » all forest fires greater than 2,000 ha in size in the years 1990 and 1991. The areal estimate derived from AVHRR data were 75% of the area mapped by the Alaska Fire Service for these years. Using fire areas and locations for 1954 through 1992, it was determined that on average, 13.0 gm-C-m-2 of boreal forest area is released during fires every year. This estimate is two to six times greater than previous reported estimates. Our conclusions are that the analysis of AVHRR data represents a viable means for detecting and mapping fires in boreal regions on a global basis.« less

Impact of atmosphere and land surface initial conditions on seasonal forecast of global surface temperature

NASA Astrophysics Data System (ADS)

Materia, Stefano; Borrelli, Andrea; Bellucci, Alessio; Alessandri, Andrea; Di Pietro, Pierluigi; Athanasiadis, Panagiotis; Navarra, Antonio; Gualdi, Silvio

2014-05-01

The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, mitigating the coupling shock and possibly increasing the model predictive skill in the ocean. In fact, in a few regions characterized by strong air-sea coupling, the atmosphere initial condition affects the forecast skill for several months. In particular, the ENSO region, the eastern tropical Atlantic and the North Pacific benefit significantly from the atmosphere initialization. On mainland, the impact of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects the forecast skill in the following lead seasons. The winter forecast in the high latitude plains of Siberia and Canada benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region, in central Asia and Australia. However, initialization through land surface reanalysis does not systematically guarantee an enhancement of the predictive skill: the quality of the forecast is sometimes higher for the non-constrained model. Overall, the introduction of a realistic initialization of land surface and atmosphere substantially increases skill and accuracy. However, further developments in the operating procedure for land surface initialization are required for more accurate seasonal forecasts.

AVHRR-Based Polar Pathfinder Products: Evaluation, Enhancement and Transition to MODIS

NASA Technical Reports Server (NTRS)

Fowler, Charles; Masalanik, James; Stone, Robert; Stroeve, Julienne; Emery, William

2001-01-01

The Advanced Very High Resolution Radiometer (AVHRR)-Based Polar Pathfinder (APP) products include calibrated AVHRR channel data, surface temperatures, albedo, satellite scan and solar geometries, and cloud mask, all composited into twice-per-day images, and daily averaged fields of sea ice motion, for regions poleward of 50 latitude. Our general goals under this grant: (1) Quantify the APP accuracy and sources of error by comparing Pathfinder products with field measurements; (2) Determine the consistency of mean fields and trends in comparison with longer time series of available station data and forecast model output; (3) Investigate the consistency of the products between the different AVHRR instruments over the 1982-present period of the NOAA program; and (4) Compare and annual cycle of the APP products with MODIS to establish a baseline for extending Pathfinder-type products into the new ESE period.

The Van Sant AVHRR image projected onto a rhombicosidodecahedron

NASA Astrophysics Data System (ADS)

Baron, Michael; Morain, Stan

1996-03-01

IDEATION, a design and development corporation, Santa Fe, New Mexico, has modeled Tom Van Sant's ``The Earth From Space'' image to a rhombicosidodecahedron. ``The Earth from Space'' image, produced by the Geosphere® Project in Santa Monica, California, was developed from hundreds of AVHRR pictures and published as a Mercator projection. IDEATION, utilizing a digitized Robinson Projection, fitted the image to foldable, paper components which, when interconnected by means of a unique tabular system, results in a rhombicosidodecahedron representation of the Earth exposing 30 square, 20 triangular, and 12 pentagonal faces. Because the resulting model is not spherical, the borders of the represented features were rectified to match the intersecting planes of the model's faces. The resulting product will be licensed and commercially produced for use by elementary and secondary students. Market research indicates the model will be used in both the demonstration of geometric principles and the teaching of fundamental spatial relations of the Earth's lands and oceans.

Long time-series of turbid coastal water using AVHRR: An example from Florida Bay, USA

USGS Publications Warehouse

Stumpf, R.P.; Frayer, M.L.

1997-01-01

The AVHRR can provide information on the reflectance of turbid case II water, permitting examination of large estuaries and plumes from major rivers. The AVHRR has been onboard several NOAA satellites, with afternoon overpasses since 1981, offering a long time-series to examine changes in coastal water. We are using AVHRR data starting in December 1989, to examine water clarity in Florida Bay, which has undergone a decline since the late 1980's. The processing involves obtaining a nominal reflectance for red light with standard corrections including those for Rayleigh and aerosol path radiances. Established relationships between reflectance and the water properties being measured in the Bay provide estimates of diffuse attenuation and light limitation for phytoplankton and seagrass productivity studies. Processing also includes monthly averages of reflectance and attenuation. The AVHRR data set describes spatial and temporal patterns, including resuspension of bottom sediments in the winter, and changes in water clarity. The AVHRR also indicates that Florida Bay has much higher reflectivity relative to attenuation than other southeastern US estuaries. ??2005 Copyright SPIE - The International Society for Optical Engineering.

Long time-series of turbid coastal water using AVHRR: an example from Florida Bay, USA

NASA Astrophysics Data System (ADS)

Stumpf, Richard P.; Frayer, M. L.

1997-02-01

The AVHRR can provide information on the reflectance of turbid case II water, permitting examination of large estuaries and plumes from major rivers. The AVHRR has been onboard several NOAA satellites, with afternoon overpasses since 1981, offering a long time-series to examine changes in coastal water. We are using AVHRR data starting in December 1989, to examine water clarity in Florida Bay, which has undergone a decline since the late 1980's. The processing involves obtaining a nominal reflectance for red light with standard corrections including those for Rayleigh and aerosol path radiances. Established relationships between reflectance and the water properties being measured in the Bay provide estimates of diffuse attenuation and light limitation for phytoplankton and seagrass productivity studies. Processing also includes monthly averages of reflectance and attenuation. The AVHRR data set describes spatial and temporal patterns, including resuspension of bottom sediments in the winter, and changes in water clarity. The AVHRR also indicates that Florida Bay has much higher reflectivity relative to attenuation than other southeastern US estuaries.

Seasonal-to-Interannual Variability and Land Surface Processes

NASA Technical Reports Server (NTRS)

Koster, Randal

2004-01-01

land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.

Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk

NASA Astrophysics Data System (ADS)

Chybicki, Andrzej; Łubniewski, Zbigniew

2017-09-01

Satellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth's environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR), using the inverse technique. The effective emissivity derived from another data source is used as a quantity describing thermal properties of the terrain in higher resolution, and allows the downsampling of low spatial resolution LST images. The authors propose an optimized downscaling method formulated as the inverse problem and show that the proposed approach yields better results than the use of other downsampling methods. The proposed method aims to find estimation of high spatial resolution LST data by minimizing the global error of the downscaling. In particular, for the investigated region of the Gulf of Gdansk, the RMSE between the AVHRR image downscaled by the proposed method and the Landsat 8 LST reference image was 2.255°C with correlation coefficient R equal to 0.828 and Bias = 0.557°C. For comparison, using the PBIM method, it was obtained RMSE = 2.832°C, R = 0.775 and Bias = 0.997°C for the same satellite scene. It also has been shown that the obtained results are also good in local scale and can be used for areas much smaller than the entire satellite imagery scene, depicting diverse biophysical conditions. Specifically, for the analyzed set of small sub-datasets of the whole scene, the obtained RSME between the downscaled and reference image was smaller, by approx. 0.53°C on average, in the case of applying the proposed method than in the case of using the PBIM method.

Alternative method to validate the seasonal land cover regions of the conterminous United States

Treesearch

Zhiliang Zhu; Donald O. Ohlen; Raymond L. Czaplewski; Robert E. Burgan

1996-01-01

An accuracy assessment method involving double sampling and the multivariate composite estimator has been used to validate the prototype seasonal land cover characteristics database of the conterminous United States. The database consists of 159 land cover classes, classified using time series of 1990 1-km satellite data and augmented with ancillary data including...

Complex seasonal patterns of primary producers at the land-sea interface

USGS Publications Warehouse

Cloern, J.E.; Jassby, A.D.

2008-01-01

Seasonal fluctuations of plant biomass and photosynthesis are key features of the Earth system because they drive variability of atmospheric CO 2, water and nutrient cycling, and food supply to consumers. There is no inventory of phytoplankton seasonal cycles in nearshore coastal ecosystems where forcings from ocean, land and atmosphere intersect. We compiled time series of phytoplankton biomass (chlorophyll a) from 114 estuaries, lagoons, inland seas, bays and shallow coastal waters around the world, and searched for seasonal patterns as common timing and amplitude of monthly variability. The data revealed a broad continuum of seasonal patterns, with large variability across and within ecosystems. This contrasts with annual cycles of terrestrial and oceanic primary producers for which seasonal fluctuations are recurrent and synchronous over large geographic regions. This finding bears on two fundamental ecological questions: (1) how do estuarine and coastal consumers adapt to an irregular and unpredictable food supply, and (2) how can we extract signals of climate change from phytoplankton observations in coastal ecosystems where local-scale processes can mask responses to changing climate? ?? 2008 Blackwell Publishing Ltd/CNRS.

Land Cover Analysis of Temperate Asia

NASA Technical Reports Server (NTRS)

Justice, Chris

1998-01-01

Satellite data from the advanced very high resolution radiometer (AVHRR) instrument were used to produce a general land cover distribution of temperate Asia (referred to hence as Central Asia) from 1982, starting with the NOAA-7 satellite, and continuing through 1991, ending with the NOAA-11 satellite. Emphasis was placed upon delineating the and and semi-arid zones of Central Asia (largely Mongolia and adjacent areas), mapping broad categories of aggregated land cover, and upon studying photosynthetic capacity increases in Central Asia from 1982 to 1991.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

Hydrologic, land cover, and seasonal patterns of waterborne pathogens in Great Lakes tributaries

USGS Publications Warehouse

Lenaker, Peter L.; Corsi, Steven; Borchardt, Mark A.; Spencer, Susan K.; Baldwin, Austin K.; Lutz, Michelle A.

2017-01-01

Great Lakes tributaries are known to deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal patterns of waterborne pathogens (i.e. protozoa (2), pathogenic bacteria (4) human viruses, (8) and bovine viruses (8)) eight rivers were monitored in the Great Lakes Basin over 29 months from February 2011 to June 2013. Sampling locations represented a wide variety of land cover classes from urban to agriculture to forest. A custom automated pathogen sampler was deployed at eight sampling locations which provided unattended, flow-weighted, large-volume (120–1630 L) sampling. Human and bovine viruses and pathogenic bacteria were detected by real-time qPCR in 16%, 14%, and 1.4% of 290 samples collected while protozoa were never detected. The most frequently detected pathogens were: bovine polyomavirus (11%), and human adenovirus C, D, F (9%). Human and bovine viruses were present in 16.9% and 14.8% of runoff-event samples (n = 189) resulting from precipitation and snowmelt, and 13.9% and 12.9% of low-flow samples (n = 101), respectively, indicating multiple delivery mechanisms could be influential. Data indicated human and bovine virus prevalence was different depending on land cover within the watershed. Occurrence, concentration, and flux of human viruses were greatest in samples from the three sampling locations with greater than 25% urban influence than those with less than 25% urban influence. Similarly, occurrence, concentration, and flux of bovine viruses were greatest in samples from the two sampling locations with greater than 50 cattle/km2 than those with less than 50 cattle/km2. In seasonal analysis, human and bovine viruses occurred more frequently in spring and winter seasons than during the fall and summer. Concentration, occurrence, and flux in the context of hydrologic condition, seasonality, and land use must be considered for each watershed individually to develop effective watershed management

The ATOVS and AVHRR product processing facility for EPS

NASA Astrophysics Data System (ADS)

Klaes, D.; Ackermann, J.; Schraidt, R.; Patterson, T.; Schlüssel, P.; Phillips, P.; Arriaga, A.; Grandell, J.

The ATOVS/AVHRR Product Processing Facility (PPF) of the EPS (EUMETSAT Polar System) Core Ground Segment comprises the Level 1 processing of the data from the ATOVS sounding instruments AMSU-A, MHS and HIRS/4, and the imager AVHRR/3 into calibrated and navigated radiances. A second component includes the level 2 processing, which uses as input the level 1 products of the aforementioned instruments. The specification of the PPF is based on two well-known and well-established software packages, which have been used by the international community for some years: The AAPP (ATOVS and AVHRR Pre-processing Package) and ICI (Inversion Coupled with Imager). The PPF is able to process data from instruments flown on the Metop and NOAA satellites. For the level 1 processing of the sounding instruments' data (HIRS, AMSU-A and MHS), the basic functionality of AAPP has been kept; however, the individual chains for each instrument have been separated and additional functionality has been integrated. For HIRS a global calibration, as performed by NOAA/NESDIS today, has been included. For AMSU-A and MHS the moon contamination of the calibration space view can be corrected for. Additional functionality has also been included in the AVHRR processing. In particular, an enhanced navigation by landmark processing has been implemented to ensure accurate geo-location. Additionally, the PPF can digest and process the global AVHRR data either at full pixel resolution (1 km at nadir), which is the nominal mode for the Metop processing, or at the reduced resolution of the NOAA/GAC (Global Area Coverage) data (about 4 km resolution at nadir). For the level 2 processing the ICI had to be modified to include the most recent improvement in fast radiative transfer modelling as included in the RTTOV-7. As a first step towards the realisation of the PPF a prototype has been generated for the purpose to help specifying the details of the PPF, and for verification of the latter by generation of

The CACAO Method for Smoothing, Gap Filling, and Characterizing Seasonal Anomalies in Satellite Time Series

NASA Technical Reports Server (NTRS)

Verger, Aleixandre; Baret, F.; Weiss, M.; Kandasamy, S.; Vermote, E.

2013-01-01

Consistent, continuous, and long time series of global biophysical variables derived from satellite data are required for global change research. A novel climatology fitting approach called CACAO (Consistent Adjustment of the Climatology to Actual Observations) is proposed to reduce noise and fill gaps in time series by scaling and shifting the seasonal climatological patterns to the actual observations. The shift and scale CACAO parameters adjusted for each season allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. CACAO was assessed first over simulated daily Leaf Area Index (LAI) time series with varying fractions of missing data and noise. Then, performances were analyzed over actual satellite LAI products derived from AVHRR Long-Term Data Record for the 1981-2000 period over the BELMANIP2 globally representative sample of sites. Comparison with two widely used temporal filtering methods-the asymmetric Gaussian (AG) model and the Savitzky-Golay (SG) filter as implemented in TIMESAT-revealed that CACAO achieved better performances for smoothing AVHRR time series characterized by high level of noise and frequent missing observations. The resulting smoothed time series captures well the vegetation dynamics and shows no gaps as compared to the 50-60% of still missing data after AG or SG reconstructions. Results of simulation experiments as well as confrontation with actual AVHRR time series indicate that the proposed CACAO method is more robust to noise and missing data than AG and SG methods for phenology extraction.

A Combined Surface Temperature Dataset for the Arctic from MODIS and AVHRR

NASA Astrophysics Data System (ADS)

Dodd, E.; Veal, K. L.; Ghent, D.; Corlett, G. K.; Remedios, J. J.

2017-12-01

Surface Temperature (ST) changes in the Polar Regions are predicted to be more rapid than either global averages or responses in lower latitudes. Observations of STs and other changes associated with climate change increasingly confirm these predictions in the Arctic. Furthermore, recent high profile events of anomalously warm temperatures have increased interest in Arctic surface temperatures. It is, therefore, particularly important to monitor Arctic climate change. Satellites are particularly relevant to observations of Polar Regions as they are well-served by low-Earth orbiting satellites. Whilst clouds often cause problems for satellite observations of the surface, in situ observations of STs are much sparser. Previous work at the University of Leicester has produced a combined land, ocean and ice ST dataset for the Arctic using ATSR data (AAST) which covers the period 1995 to 2012. In order to facilitate investigation of more recent changes in the Arctic (2010 to 2016) we have produced another combined surface temperature dataset using MODIS and AVHRR; the Metop-A AVHRR and MODIS Arctic Surface Temperature dataset (AMAST). The method of cloud-clearing, use of auxiliary data for ice classification and the ST retrievals used for each surface-type in AMAST will be described. AAST and AMAST were compared in the time period common to both datasets. We will provide results from this intercomparison, as well as an assessment of the impact of utilising data from wide and narrow swath sensors. Time series of ST anomalies over the Arctic region produced from AMAST will be presented.

Alternative Approaches to Land Initialization for Seasonal Precipitation and Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, Randal; Suarez, Max; Liu, Ping; Jambor, Urszula

2004-01-01

The seasonal prediction system of the NASA Global Modeling and Assimilation Office is used to generate ensembles of summer forecasts utilizing realistic soil moisture initialization. To derive the realistic land states, we drive offline the system's land model with realistic meteorological forcing over the period 1979-1993 (in cooperation with the Global Land Data Assimilation System project at GSFC) and then extract the state variables' values on the chosen forecast start dates. A parallel series of forecast ensembles is performed with a random (though climatologically consistent) set of land initial conditions; by comparing the two sets of ensembles, we can isolate the impact of land initialization on forecast skill from that of the imposed SSTs. The base initialization experiment is supplemented with several forecast ensembles that use alternative initialization techniques. One ensemble addresses the impact of minimizing climate drift in the system through the scaling of the initial conditions, and another is designed to isolate the importance of the precipitation signal from that of all other signals in the antecedent offline forcing. A third ensemble includes a more realistic initialization of the atmosphere along with the land initialization. The impact of each variation on forecast skill is quantified.

Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

NASA Technical Reports Server (NTRS)

Bolle, H.-J.; Koslowsky, D.; Menenti, M.; Nerry, F.; Otterman, Joseph; Starr, D.

1998-01-01

Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

Calibrating Historical IR Sensors Using GEO, and AVHRR Infrared Tropical Mean Calibration Models

NASA Technical Reports Server (NTRS)

Scarino, Benjamin; Doelling, David R.; Minnis, Patrick; Gopalan, Arun; Haney, Conor; Bhatt, Rajendra

2014-01-01

Long-term, remote-sensing-based climate data records (CDRs) are highly dependent on having consistent, wellcalibrated satellite instrument measurements of the Earth's radiant energy. Therefore, by making historical satellite calibrations consistent with those of today's imagers, the Earth-observing community can benefit from a CDR that spans a minimum of 30 years. Most operational meteorological satellites rely on an onboard blackbody and space looks to provide on-orbit IR calibration, but neither target is traceable to absolute standards. The IR channels can also be affected by ice on the detector window, angle dependency of the scan mirror emissivity, stray-light, and detector-to-detector striping. Being able to quantify and correct such degradations would mean IR data from any satellite imager could contribute to a CDR. Recent efforts have focused on utilizing well-calibrated modern hyper-spectral sensors to intercalibrate concurrent operational IR imagers to a single reference. In order to consistently calibrate both historical and current IR imagers to the same reference, however, another strategy is needed. Large, well-characterized tropical-domain Earth targets have the potential of providing an Earth-view reference accuracy of within 0.5 K. To that effort, NASA Langley is developing an IR tropical mean calibration model in order to calibrate historical Advanced Very High Resolution Radiometer (AVHRR) instruments. Using Meteosat-9 (Met-9) as a reference, empirical models are built based on spatially/temporally binned Met-9 and AVHRR tropical IR brightness temperatures. By demonstrating the stability of the Met-9 tropical models, NOAA-18 AVHRR can be calibrated to Met-9 by matching the AVHRR monthly histogram averages with the Met-9 model. This method is validated with ray-matched AVHRR and Met-9 biasdifference time series. Establishing the validity of this empirical model will allow for the calibration of historical AVHRR sensors to within 0.5 K, and thereby

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to

Relating seasonal patterns of the AVHRR vegetation index to simulated photosynthesis and transpiration of forests in different climates

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.

1988-01-01

Weekly AVHRR Normalized Difference Vegetation Index (NDVI) values for 1983-1984 for seven sites of diverse climate in North America were correlated with results of an ecosystem simulation model of a hypothetical forest stand for the corresponding period at each site. The tendency of raw NDVI data to overpredict photosynthesis and transpiration on water limited sites was shown to be partially corrected by using an aridity index of annual radiation/annual precipitation. The results suggest that estimates of vegetation productivity using the global vegetation index are only accurate as annual integrations, unless unsubsampled local area coverage NDVI data can be tested against forest photosynthesis, transpiration and aboveground net primary production data measured at shorter time intervals.

Aerosol Correction for Remotely Sensed Sea Surface Temperatures From the NOAA AVHRR: Phase II

NASA Astrophysics Data System (ADS)

Nalli, N. R.; Ignatov, A.

2002-05-01

For over two decades, the National Oceanic and Atmospheric Administration (NOAA) has produced global retrievals of sea surface temperature (SST) using infrared (IR) data from the Advanced Very High Resolution Radiometer (AVHRR). The standard multichannel retrieval algorithms are derived from regression analyses of AVHRR window channel brightness temperatures against in situ buoy measurements under non-cloudy conditions thus providing a correction for IR attenuation due to molecular water vapor absorption. However, for atmospheric conditions with elevated aerosol levels (e.g., arising from dust, biomass burning and volcanic eruptions), such algorithms lead to significant negative biases in SST because of IR attenuation arising from aerosol absorption and scattering. This research presents the development of a 2nd-phase aerosol correction algorithm for daytime AVHRR SST. To accomplish this, a long-term (1990-1998), global AVHRR-buoy matchup database was created by merging the Pathfinder Atmospheres (PATMOS) and Oceans (PFMDB) data sets. The merged data are unique in that they include multi-year, global daytime estimates of aerosol optical depth (AOD) derived from AVHRR channels 1 and 2 (0.63 and 0.83 μ m, respectively), along with an effective Angstrom exponent derived from the AOD retrievals (Ignatov and Nalli, 2002). Recent enhancements in the aerosol data constitute an improvement over the Phase I algorithm (Nalli and Stowe, 2002) which relied only on channel 1 AOD and the ratio of normalized reflectance from channels 1 and 2. The Angstrom exponent and channel 2 AOD provide important statistical information about the particle size distribution of the aerosol. The SST bias can be parametrically expressed as a function of observed AVHRR channels 1 and 2 slant-path AOD, normalized reflectance ratio and the Angstrom exponent. Based upon these empirical relationships, aerosol correction equations are then derived for the daytime multichannel and nonlinear SST (MCSST

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1994-01-01

During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

Linear and nonlinear trending and prediction for AVHRR time series data

NASA Technical Reports Server (NTRS)

Smid, J.; Volf, P.; Slama, M.; Palus, M.

1995-01-01

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

EFFECTS OF LAND USE AND SEASON ON MICROORGANISM CONCENTRATIONS IN URBAN STORMWATER RUNOFF

EPA Science Inventory

This study investigated differences in pathogen and indicator organism concentrations in stormwater runoff between different urban land uses and seasons. Stormwater samples collected from storm sewers draining small municipal separate storm sewer systems shown to be free of cros...

BOREAS Level 3-b AVHRR-LAC Imagery: Scaled At-sensor Radiance in LGSOWG Format

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime; Newcomer, Jeffrey A.; Cihlar, Josef

2000-01-01

The BOREAS Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Data acquired from the AVHRR instrument on the NOAA-9, -11, -12, and -14 satellites were processed and archived for the BOREAS region by the MRSC and BORIS. The data were acquired by CCRS and were provided for use by BOREAS researchers. A few winter acquisitions are available, but the archive contains primarily growing season imagery. These gridded, at-sensor radiance image data cover the period of 30-Jan-1994 to 18-Sep-1996. Geographically, the data cover the entire 1,000-km x 1,000-km BOREAS region. The data are stored in binary image format files.

Comparison between AVHRR surface temperature data and in-situ weather station temperatures over the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, S.; Csatho, B. M.; Comiso, J. C.; Babonis, G. S.

2011-12-01

Advanced Very-High Resolution Radiometer (AVHRR) images have been exhaustively used to measure surface temperature time series of the Greenland Ice sheet. The purpose of this study is to assess the accuracy of monthly average ice sheet surface temperatures, derived from thermal infrared AVHRR satellite imagery on a 6.25 km grid. In-situ temperature data sets are from the Greenland Collection Network (GC-Net). GC-Net stations comprise sensors monitoring air temperature at 1 and 2 meter above the snow surface, gathered at every 60 seconds and monthly averaged to match the AVHRR temporal resolution. Our preliminary results confirm the good agreement between satellite and in-situ temperature measurements reported by previous studies. However, some large discrepancies still exist. While AVHRR provides ice surface temperature, in-situ stations measure air temperatures at different elevations above the snow surface. Since most in-situ data on ice sheets are collected by Automatic Weather Station (AWS) instruments, it is important to characterize the difference between surface and air temperatures. Therefore, we compared and analyzed average monthly AVHRR ice surface temperatures using data collected in 2002. Differences between these temperatures correlate with in-situ temperatures and GC-Net station elevations, with increasing differences at lower elevations and higher temperatures. The Summit Station (3199 m above sea level) and the Swiss Camp (1176 m above sea level) results were compared as high altitude and low altitude stations for 2002, respectively. Our results show that AVHRR derived temperatures were 0.5°K warmer than AWS temperature at the Summit Station, while this difference was 2.8°K in the opposite direction for the Swiss Camp with surface temperatures being lower than air temperatures. The positive bias of 0.5°K at the high altitude Summit Station (surface warmer than air) is within the retrieval error of AVHRR temperatures and might be in part due to

Linkages between Snow Cover Seasonality, Terrain, and Land Surface Phenology in the Highland Pastures of Kyrgyzstan

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey; Tomaszewska, Monika; Kelgenbaeva, Kamilya

2017-04-01

In the highlands of Kyrgyzstan, vertical transhumance is the foundation of montane agropastoralism. Terrain attributes, such as elevation, slope, and aspect, affect snow cover seasonality, which is a key influence on the timing of plant growth and forage availability. Our study areas include the highland pastures in Central Tien Shan mountains, specifically in the rayons of Naryn and At-Bashy in Naryn oblast, and Alay and Chong-Alay rayons in Osh oblast. To explore the linkages between snow cover seasonality and land surface phenology as modulated by terrain and variations in thermal time, we use 16 years (2001-2016) of Landsat surface reflectance data at 30 m resolution with MODIS land surface temperature and snow cover products at 1 km and 500 m resolution, respectively, and two digital elevation models, SRTM and ASTER GDEM. We model snow cover seasonality using frost degree-days and land surface phenology using growing degree-days as quadratic functions of thermal time: a convex quadratic (CxQ) model for land surface phenology and a concave quadratic (CvQ) model for snow cover seasonality. From the fitted parameter coefficients, we calculated phenometrics, including "peak height" and "thermal time to peak" for the CxQ models and "trough depth" and "thermal time to trough" for the CvQ models. We explore how these phenometrics change as a function of elevation and slope-aspect interactions and due to interannual variability. Further, we examine how snow cover duration and timing affects the subsequent peak height and thermal time to peak in wetter, drier, and normal years.

Seasonal variation in standardized litter decomposition and effects of elevation and land use at Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Becker, Joscha; Kuzyakov, Yakov

2017-04-01

Decomposition is one of most important ecological steps in organic matter and nutrient cycles, but studies and reliable data from tropical regions in Africa are still scarce. At the global scale, litter decomposition and recycling is controlled by climatic factors and land-use intensity. These factors can be linked to specific ecosystem characteristics along the unique elevation gradient of Mt. Kilimanjaro. Our objectives were to assess the effects of climatic conditions (i.e. elevation) and land-use intensity on C turnover and stabilization and investigated the seasonal variations. Tea-bag Index (see www.teatime4science.org) was used to measure decomposition of a standardized litter substrate by microorganisms and mesofauna <0.25 mm. Nine pairs of litterbags were exposed in eleven ecosystems for 90 days during the short-rainy (October-December), warm-dry (December-March), long-rainy (March-July) and cold-dry season (July-September) respectively. Decomposition rates increased from k=0.007 in savanna, up to a maximum of k=0.022 in cloud forest (i.e. mid elevation). The increase was followed by a decrease of 50% in (sub-) alpine ecosystems. Stabilization factors decreased from savanna (S=0.33) to coffee plantations or cloud forest (S=0.11) respectively and strongly increased again to a maximum of S=0.41 in the alpine helichrysum ecosystem. During all seasons, we found the highest decomposition rates at mid elevation. However, during both warm seasons the peak is shifted upslope. Savanna experienced the strongest seasonal variation, with 23 times higher S-values in dry- compared to rainy season. Mean annual k-values increased for about 30% with increasing land-use intensity. C stabilization in Mt. Kilimanjaro ecosystems is strongly dependent on seasonal moisture limitation (lower slope) and perennial temperature limitation (alpine zone). Ecosystems at mid elevation (around 1920 & 2120m) represent the interception zone of optimal moisture and temperature conditions

Monitoring Italian volcanoes by NOAA-AVHRR satellite data

NASA Astrophysics Data System (ADS)

Spinetti, C.; Buongiorno, M. F.; Amici, S.; Silvestri, M.; Lombardo, V.; Musacchio, M.; Doumaz, F.; Corradini, C.

2009-04-01

The INGV Remote Sensing unit is equipped with a NOAA-AVHRR receiving station that provides 4 to 10 images per day of the central Mediterranean area in the visible to thermal infrared bands. These data were acquired and processed in real time using automatic and semi-automatic procedures which outputs information collated in daily and weekly observation reports and outputs overview images in the DPC dedicated web page. Satellite information included the presence of hot spots as well as their temporal evolution in terms of temperature. An automatic procedure that calculate lava flow effusion rate has been developed. The procedure automatically sent alert via e-mail when an hot spot is present in the AVHRR data. Volcanic ash information AVHRR-derived has been also included in a separate system. These information concerned the presence of volcanic ash in air, an assessment of the area affected, as well as the plume dispersal direction, the ash plume altitude and the concentration of ash in air. The eruptions occurred both at Etna and Stromboli volcanoes in Sicily (Italy) has been surveyed by satellite. The different eruptions were characterized both by lava flow emissions and eruption of ash plumes with different impact to the surrounding villages and cities, causing problems to local communications and air traffic. Information provided by satellite sensors are communicate in observation reports integrating ground-based surveillance operated by INGV Catania Volcanology Observatory in agreement with the Italian Department of Civil Protection (DPC) responsible for volcanic risk and airports closure during the explosive phases.

BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters

NASA Technical Reports Server (NTRS)

Cihlar, Josef; Chen, Jing; Huang, Fengting; Nickeson, Jaime; Newcomer, Jeffrey A.; Hall, Forrest G. (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day composites of surface parameters produced from sets of single-day images. Temporally, the 10-day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files. Note: Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program.

Developing NOAA's Climate Data Records From AVHRR and Other Data

NASA Astrophysics Data System (ADS)

Privette, J. L.; Bates, J. J.; Kearns, E. J.

2010-12-01

As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm

Vegetation monitoring and classification using NOAA/AVHRR satellite data

NASA Technical Reports Server (NTRS)

Greegor, D. H., Jr.; Norwine, J. R.

1983-01-01

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

BOREAS Level-4b AVHRR-LAC Ten-Day Composite Images: At-sensor Radiance

NASA Technical Reports Server (NTRS)

Cihlar, Josef; Chen, Jing; Nickerson, Jaime; Newcomer, Jeffrey A.; Huang, Feng-Ting; Hall, Forrest G. (Editor)

2000-01-01

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the National Oceanic and Atmospheric Administration (NOAA-11) and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4b data are gridded, 10-day composites of at-sensor radiance values produced from sets of single-day images. Temporally, the 10- day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files.

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, M. J.; Heiser, M.

1998-01-01

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

Non-growing season soil CO2 efflux patterns in five land-use types in northern China

USDA-ARS?s Scientific Manuscript database

Overgrazing and unsuitable farming practices have led to grassland degradation in northern China. This studhy examined soil CO2 efflux (Fc) from five land-use types during the non-growing season on the southeastern edge of the Mongolian Plateau in China. The land-use types included three native v...

An AVHRR Cloud Classification Database Typed by Experts

DTIC Science & Technology

1993-10-01

analysis. Naval Research Laboratory, Monterey, CA. 110 pp. Gallaudet , Timothy C. and James J. Simpson, 1991: Automated cloud screening of AVHRR imagery...1987) and Saunders and Kriebel (1988a,b) have used threshold techniques to classify clouds. Gallaudet and Simpson (1991) have used split-and-merge

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

NASA Technical Reports Server (NTRS)

Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.

2016-01-01

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

Hydrologic, land cover and seasonal patterns of waterborne pathogens in great lakes tributaries

USDA-ARS?s Scientific Manuscript database

Great Lakes tributaries deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal variability of waterborne pathogens, protozoa (2), pathogenic bacteria (4) and human (8) and bovine (8) viruses from eight rivers were monitored in the Great Lakes watersh...

Neural Networks as a Tool for Constructing Continuous NDVI Time Series from AVHRR and MODIS

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Lary, David J.; Vrieling, Anton; Stathakis, Demetris; Mussa, Hamse

2008-01-01

The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

Characterizing the Responses of Land Surface Phenology to the Rainy Season in the Congo Basin

NASA Astrophysics Data System (ADS)

Yan, D.; Zhang, X.; Yu, Y.; Guo, W.

2016-12-01

The most pronounced climate changes across the Congo Basin are predicted to be the changes in the timing and amount of rainfall in the coming decades. It is expected to alter a significant shift in land surface phenology (LSP), so that an understanding of its responses to the rainy season can benefit the predictions of changes in the Congolese ecosystem under future climate change scenarios. However, quantitative analyses has not been performed to investigate the relationship between LSP and the rainy season in the Congo Basin. Based on 30-minute observations acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the METEOSAT Second Generation series of geostationary satellites, we generated a time series of three-day angularly corrected Two-band Enhanced Vegetation Index (EVI2) between 2006 and 2013. We then reconstructed EVI2 temporal trajectories and retrieved the timings and magnitudes of LSP using the hybrid piecewise logistic model. We further associated the phenological timings and magnitudes with those of the rainy seasons derived from the three-hourly rainfall rate measurements provided by the Tropical Rainfall Measurement Mission Product 3B42. Finally, we investigated the impacts of tree cover on the timing discrepancy between LSP and the rainy season. Results show that LSP was strongly associated with the rainy season. Specifically, the SEVIRI EVI2 time series reveals that two annual canopy greenness cycles (CGC) occur in the Congolese rainforests whereas a single annual CGC with strong seasonal amplitude was identified for other land cover types. The spatial shifts in CGC timings closely follow those of the rainy season controlled by the seasonal migration of the Intertropical Convergence Zone. However, the tree cover controls the timing discrepancy between LSP and the rainy season. The accumulated vegetation greenness during a CGC shows a strong dependence on the total rainfall received.

Derivation of Coefficients for the Bidirectional Reflection Distribution Function from AVHRR-data over Europe, under Consideration of the Helmholtz Reciprocity Law

NASA Astrophysics Data System (ADS)

Billing, H.; Koslowsky, D.

In the AVHRR data of the polar orbiting NOAA Satellites, directional reflectance under a certain view from satellite and a certain illumination by the sun is measured. Due to the nearly sunsynchroneous orbit of the NOAA satellite, each area is seen under different viewing angles in successive days. Only after approximately 9 days, the conditions are again similar. Areas, seen in specular direction, may appear only half as bright, as if seen in antispecular direction. This deviation from a Lambertian reflector is a function of the surface roughness and the degree of coverage with vegetation. The NOAA afternoon satellites drift by half an hour from year to year. Thus even data from the same season, but different years, are seen under different illumination conditions. To derive the bidirectional reflection distribution function in dependence on satellite viewing angle and solar illumination becomes a very complicated procedure. Using the Helmholtz reciprocity principle (HRP), i.e. the symetrie in viewing and illumination, reduces the problem by one dimension. For different bidimensional reflection laws it will be tested, whether they can be formulated to fullfill the HRP. Via regression, the parameters will be deduced for time series of AVHRR data of 10 years from NOAA 11,14,16 and 17. Brdfunctions, suggested by Rao as well as a law, suggested by Ba seem to become unstable for low sun resp. large viewing zenit angles. Only brdfs with 4 coefficients can fit the observed distributions. A nonlinear temporal angular model (NTAM), suggested by Latifovic,Cihlar and Chen, seems to be suitable to describe even the hot spot and the dependence on plant growth. The coefficients of these brdf-function will be derived via regression for monthly series of cloud free data for the European area, where AVHRR data in full resolution are received in Berlin. Using these coefficients, monthly maps of surface roughness are produced for the above area for the time since 1985. Ba, M

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

NASA Technical Reports Server (NTRS)

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

1987-01-01

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

Remote sensing of ephemeral water bodies in western Niger

USGS Publications Warehouse

Verdin, J.P.

1996-01-01

Research was undertaken to evaluate the feasibility of monitoring the small ephemeral water bodies of the Sahel with the 1.1 km resolution data of the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). Twenty-one lakes of western Niger with good ground observation records were selected for examination. Thematic Mapper images from 1988 were first analysed to determine surface areas and temperature differences between water and adjacent land. Six AVHRR scenes from the 1988-89 dry season were then studied. It was found that a lake can be monitored until its surface area drops below 10 ha, in most cases. Furthermore, with prior knowledge of the location and shape of a water body, its surface area can be estimated from AVHRR band 5 data to within about 10 ha. These results are explained by the sharp temperature contrast between water and land, on the order of 13?? C.

On the Use of Deep Convective Clouds to Calibrate AVHRR Data

NASA Technical Reports Server (NTRS)

Doelling, David R.; Nguyen, Louis; Minnis, Patrick

2004-01-01

Remote sensing of cloud and radiation properties from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellites requires constant monitoring of the visible sensors. NOAA satellites do not have onboard visible calibration and need to be calibrated vicariously in order to determine the calibration and the degradation rate. Deep convective clouds are extremely bright and cold, are at the tropopause, have nearly a Lambertian reflectance, and provide predictable albedos. The use of deep convective clouds as calibration targets is developed into a calibration technique and applied to NOAA-16 and NOAA-17. The technique computes the relative gain drift over the life-span of the satellite. This technique is validated by comparing the gain drifts derived from inter-calibration of coincident AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) radiances. A ray-matched technique, which uses collocated, coincident, and co-angled pixel satellite radiance pairs is used to intercalibrate MODIS and AVHRR. The deep convective cloud calibration technique was found to be independent of solar zenith angle, by using well calibrated Visible Infrared Scanner (VIRS) radiances onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, which precesses through all solar zenith angles in 23 days.

Influence of seasonal cycles in Martian atmosphere on entry, descent and landing sequence

NASA Astrophysics Data System (ADS)

Marčeta, Dušan; Šegan, Stevo; Rašuo, Boško

2014-05-01

The phenomena like high eccentricity of Martian orbit, obliquity of the orbital plane and close alignment of the winter solstice and the orbital perihelion, separately or together can significantly alter not only the level of some Martian atmospheric parameters but also the characteristics of its diurnal and seasonal cycle. Considering that entry, descent and landing (EDL) sequence is mainly driven by the density profile of the atmosphere and aerodynamic characteristic of the entry vehicle. We have performed the analysis of the influence of the seasonal cycles of the atmospheric parameters on EDL profiles by using Mars Global Reference Atmospheric Model (Mars-GRAM). Since the height of the deployment of the parachute and the time passed from the deployment to propulsion firing (descent time) are of crucial importance for safe landing and the achievable landing site elevation we paid special attention to the influence of the areocentric longitude of the Sun (Ls) on these variables. We have found that these variables have periodic variability with respect to Ls and can be very well approximated with a sine wave function whose mean value depends only on the landing site elevation while the amplitudes and phases depend only on the landing site latitude. The amplitudes exhibit behavior which is symmetric with respect to the latitude but the symmetry is shifted from the equator to the northern mid-tropics. We have also noticed that the strong temperature inversions which are usual for middle and higher northern latitudes while Mars is around its orbital perihelion significantly alter the descent time without influencing the height of the parachute deployment. At last, we applied our model to determine the dependence of the accessible landing region on Ls and found that this region reaches maximum when Mars is around the orbital perihelion and can vary 50° in latitude throughout the Martian year.

Land cover characterization and mapping of continental southeast Asia using multi-resolution satellite sensor data

USGS Publications Warehouse

Giri, Chandra; Defourny, Pierre; Shrestha, Surendra

2003-01-01

Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.

Relation of pesticide concentrations to season, streamflow, and land use in seven New Jersey streams

USGS Publications Warehouse

Reiser, Robert G.

1999-01-01

concentrations that exceeded New Jersey Department of Environmental Protection (NJDEP) human health criteria. Individual and total-pesticide concentrations and total numbers of pesticides detected in the samples varied with season and flow conditions. Median and maximum concentrations of most of the pesticides were highest during runoff in the growing season. Pesticide concentrations were typically lower and less variable in the nongrowing season than in the growing season, regardless of changes in hydrologic conditions; however, median concentrations of most pesticides were slightly lower during runoff than during base flow. The median total-pesticide concentration and median total number of pesticides detected were highest and most variable in runoff samples in the growing season. In the nongrowing season, the median total-pesticide concentration was lowest in runoff samples and least variable during base-flow conditions. Median total numbers of pesticides were lowest and least varibale in the nongrowing season during base-flow conditions at most sites. The highest total-pesticide concentrations were detected in samples from the two small agricultural basins (greater than 25 percent of land use is agricultural) during runoff in late spring and early summer. In general, insecticides were detected more frequently and in greater concentrations at urban sites. Concentrations of agricultural herbicides generally decreased with increasing flow at the four sites with less than 10 percent agriculture land use and increased with increasing flow at the three sites with more than 25 percent agricultural land use. Most of the pesticides that correlated positively with streamflow were detected at sites where land use in the basin would indicate the use of those particular pesticides. Most of the pesticides that correlated negatively with streamflow were present at the site in the Coastal Plain or at sites in which the land use in the basin would not indicate heavy u

A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Yu, Y.; Liu, L.

2015-12-01

Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

Sea ice motions in the Central Arctic pack ice as inferred from AVHRR imagery

NASA Technical Reports Server (NTRS)

Emery, William; Maslanik, James; Fowler, Charles

1995-01-01

Synoptic observations of ice motion in the Arctic Basin are currently limited to those acquired by drifting buoys and, more recently, radar data from ERS-1. Buoys are not uniformly distributed throughout the Arctic, and SAR coverage is currently limited regionally and temporally due to the data volume, swath width, processing requirements, and power needs of the SAR. Additional ice-motion observations that can map ice responses simultaneously over large portions of the Arctic on daily to weekly time intervals are thus needed to augment the SAR and buoys data and to provide an intermediate-scale measure of ice drift suitable for climatological analyses and ice modeling. Principal objectives of this project were to: (1) demonstrate whether sufficient ice features and ice motion existed within the consolidated ice pack to permit motion tracking using AVHRR imagery; (2) determine the limits imposed on AVHRR mapping by cloud cover; and (3) test the applicability of AVHRR-derived motions in studies of ice-atmosphere interactions. Each of these main objectives was addressed. We conclude that AVHRR data, particularly when blended with other available observations, provide a valuable data set for studying sea ice processes. In a follow-on project, we are now extending this work to cover larger areas and to address science questions in more detail.

A Consistent AVHRR Visible Calibration Record Based on Multiple Methods Applicable for the NOAA Degrading Orbits. Part 2 ; Validation

NASA Technical Reports Server (NTRS)

Doelling, David R.; Bhatt, Rajendra; Scarino, Benjamin R.; Gopalan, Arun; Haney, Conor O.; Minnis, Patrick; Bedka, Kristopher M.

2016-01-01

Consistent cross-sensor Advanced Very High Resolution Radiometer (AVHRR) calibration coefficients are determined using desert, polar ice, and deep convective cloud (DCC) invariant Earth targets. The greatest AVHRR calibration challenge is the slow orbit degradation of the host satellite, which precesses toward a terminator orbit. This issue is solved by characterizing the invariant targets with NOAA-16 AVHRR observed radiances that have been referenced to the Aqua Moderate Resolution Imaging Spectrometer (MODIS) calibration using simultaneous nadir overpass (SNO) observations. Another benefit of the NOAA-16 invariant target-modeled reflectance method is that, because of the similarities among the AVHRR spectral response functions, a smaller spectral band adjustment factor is required than when establishing calibrations relative to a non-AVHRR reference instrument. The sensor- and band-specific calibration uncertainties, with respect to the calibration reference, are, on average, 2 percent and 3 percent for channels 1 and 2, respectively. The uncertainties are smaller for sensors that are in afternoon orbits, have longer records, and spend less time in terminator conditions. The multiple invariant targets referenced to Aqua MODIS (MITRAM) AVHRR calibration coefficients are evaluated for individual target consistency, compared against Aqua MODIS/AVHRR SNOs, and selected published calibration gains. The MITRAM and SNO relative calibration biases mostly agree to within 1 percent for channels 1 and 2, respectively. The individual invariant target and MITRAM sensor relative calibration biases are mostly consistent to within 1 percent and 2 percent for channels 1 and 2, respectively. The differences between the MITRAM and other published calibrations are mostly attributed to the reference instrument calibration differences.

LAI, FAPAR and FCOVER products derived from AVHRR long time series: principles and evaluation

NASA Astrophysics Data System (ADS)

Verger, A.; Baret, F.; Weiss, M.; Lacaze, R.; Makhmara, H.; Pacholczyk, P.; Smets, B.; Kandasamy, S.; Vermote, E.

2012-04-01

Continuous and long term global monitoring of the terrestrial biosphere has draught an intense interest in the recent years in the context of climate and global change. Developing methodologies for generating historical data records from data collected with different satellite sensors over the past three decades by taking benefits from the improvements identified in the processing of the new generation sensors is a new central issue in remote sensing community. In this context, the Bio-geophysical Parameters (BioPar) service within Geoland2 project (http://www.geoland2.eu) aims at developing pre-operational infrastructures for providing global land products both in near real time and off-line mode with long time series. In this contribution, we describe the principles of the GEOLAND algorithm for generating long term datasets of three key biophysical variables, leaf area index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) and cover fraction (FCOVER), that play a key role in several processes, including photosynthesis, respiration and transpiration. LAI, FAPAR and FCOVER are produced globally from AVHRR Long Term Data Record (LTDR) for the 1981-2000 period at 0.05° spatial resolution and 10 days temporal sampling frequency. The proposed algorithm aims to ensure robustness of the derived long time series and consistency with the ones developed in the recent years, and particularly with GEOLAND products derived from VEGETATION sensor. The approach is based on the capacity of neural networks to learn a particular biophysical product (GEOLAND) from reflectances from another sensor (AVHRR normalized reflectances in the red and near infrared bands). Outliers due to possible cloud contamination or residual atmospheric correction are iteratively eliminated. Prior information based on the climatology is used to get more robust estimates. A specific gap filing and smoothing procedure was applied to generate continuous and smooth time series of decadal

Detecting Land Cover Change by Trend and Seasonality of Remote Sensing Time Series

NASA Astrophysics Data System (ADS)

Oliveira, J. C.; Epiphanio, J. N.; Mello, M. P.

2013-05-01

Natural resource managers demand knowledge of information on the spatiotemporal dynamics of land use and land cover change, and detection and characteristics change over time is an initial step for the understanding of the mechanism of change. The propose of this research is the use the approach BFAST (Breaks For Additive Seasonal and Trend) for detects trend and seasonal changes within Normalized Difference Vegetation Index (NDVI) time series. BFAST integrates the decomposition of time series into trend, seasonal, and noise components with methods for detecting change within time series without the need to select a reference period, set a threshold, or define a change trajectory. BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction. The general model is of the form Yt = Tt + St + et (t= 1,2,3,…, n) where Yt is the observed data at time t, Tt is the trend component, St is the seasonal component, and et is the remainder component. In this study was used MODIS NDVI time series datasets (MOD13Q1) over 11 years (2000 - 2010) on an intensive agricultural area in Mato Grosso - Brazil. At first it was applied a filter for noise reduction (4253H twice) over spectral curve of each MODIS pixel, and subsequently each time series was decomposed into seasonal, trend, and remainder components by BFAST. Were detected one abrupt change from a single pixel of forest and two abrupt changes on trend component to a pixel of the agricultural area. Figure 1 shows the number of phonological change with base in seasonal component for study area. This paper demonstrated the ability of the BFAST to detect long-term phenological change by analyzing time series while accounting for abrupt and gradual changes. The algorithm iteratively estimates the dates and number of changes occurring within seasonal and trend components, and characterizes changes by extracting the magnitude and direction of change. Changes occurring in the

Automatic AVHRR image navigation software

NASA Technical Reports Server (NTRS)

Baldwin, Dan; Emery, William

1992-01-01

This is the final report describing the work done on the project entitled Automatic AVHRR Image Navigation Software funded through NASA-Washington, award NAGW-3224, Account 153-7529. At the onset of this project, we had developed image navigation software capable of producing geo-registered images from AVHRR data. The registrations were highly accurate but required a priori knowledge of the spacecraft's axes alignment deviations, commonly known as attitude. The three angles needed to describe the attitude are called roll, pitch, and yaw, and are the components of the deviations in the along scan, along track and about center directions. The inclusion of the attitude corrections in the navigation software results in highly accurate georegistrations, however, the computation of the angles is very tedious and involves human interpretation for several steps. The technique also requires easily identifiable ground features which may not be available due to cloud cover or for ocean data. The current project was motivated by the need for a navigation system which was automatic and did not require human intervention or ground control points. The first step in creating such a system must be the ability to parameterize the spacecraft's attitude. The immediate goal of this project was to study the attitude fluctuations and determine if they displayed any systematic behavior which could be modeled or parameterized. We chose a period in 1991-1992 to study the attitude of the NOAA 11 spacecraft using data from the Tiros receiving station at the Colorado Center for Astrodynamic Research (CCAR) at the University of Colorado.

Radiation energy budget studies using collocated AVHRR and ERBE observations

NASA Technical Reports Server (NTRS)

Ackerman, Steven A.; Inoue, Toshiro

1994-01-01

Changes in the energy balance at the top of the atmosphere are specified as a function of atmospheric and surface properties using observations from the Advanced Very High Resolution Radiometer (AVHRR) and the Earth Radiation Budget Experiment (ERBE) scanner. By collocating the observations from the two instruments, flown on NOAA-9, the authors take advantage of the remote-sensing capabilities of each instrument. The AVHRR spectral channels were selected based on regions that are strongly transparent to clear sky conditions and are therefore useful for characterizing both surface and cloud-top conditions. The ERBE instruments make broadband observations that are important for climate studies. The approach of collocating these observations in time and space is used to study the radiative energy budget of three geographic regions: oceanic, savanna, and desert.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1995-01-01

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Snow and Ice Applications of AVHRR in Polar Regions: Report of a Workshop

NASA Technical Reports Server (NTRS)

Steffen, K.; Bindschadler, R.; Casassa, G.; Comiso, J.; Eppler, D.; Fetterer, F.; Hawkins, J.; Key, J.; Rothrock, D.; Thomas, R.;

Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

PubMed

Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

2015-07-01

Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

The role of land use/land cover dependent preferential flow paths in hydrologic response of steep and seasonal tropical catchments

NASA Astrophysics Data System (ADS)

Cheng, Y.; Ogden, F. L.; Zhu, J.

2017-12-01

The hydrologic behavior of steep catchments with saprolitic soils in the humid seasonal tropics varies with land use and cover, even when they have identical topographic index and slope distributions, underlying geology and soils textures. Forested catchments can produce more baseflow during the dry season compared to catchments containing substantial amount of pasture, the so-called "sponge effect". During rainfall events, forested catchments can also exhibit lower peak runoff rates and runoff efficiencies compared to pasture catchments. We hypothesize that hydrologic effects of land use arise from differences in preferential flow paths (PFPs) formed by biotic and abiotic factors in the upper one to two meters of soil and that land use effects on hydrological response are described by the relative amounts of forest and pasture within a catchment. Furthermore, we hypothesize that infiltration measurements at different scales allow estimation of PFP-related parameters. These hypotheses are tested by a model that explicitly simulates PFPs using distinct input parameter sets for forest and pasture. Runoff observations from three catchments with pasture, forest, and a mosaic of subsistence agricultural land covers allow model evaluation. Multiple objective criteria indicate that field measurements of infiltration enable PFP-relevant parameter identification and that pasture and forest end member parameter sets describe much of the observed difference. Analysis of water balance components and comparison between average transient water table depth and vertical PFP flow capacity demonstrate that the interplay of lateral and vertical PFPs contribute to the sponge-effect and can explain differences in peak runoff and runoff efficiency.

Development of a land-cover characteristics database for the conterminous U.S.

USGS Publications Warehouse

Loveland, Thomas R.; Merchant, J.W.; Ohlen, D.O.; Brown, Jesslyn F.

1991-01-01

Information regarding the characteristics and spatial distribution of the Earth's land cover is critical to global environmental research. A prototype land-cover database for the conterminous United States designed for use in a variety of global modelling, monitoring, mapping, and analytical endeavors has been created. The resultant database contains multiple layers, including the source AVHRR data, the ancillary data layers, the land-cover regions defined by the research, and translation tables linking the regions to other land classification schema (for example, UNESCO, USGS Anderson System). The land-cover characteristics database can be analyzed, transformed, or aggregated by users to meet a broad spectrum of requirements. -from Authors

NASA Cold Land Processes Experiment (CLPX 2002/03): Spaceborne remote sensing

Treesearch

Robert E. Davis; Thomas H. Painter; Don Cline; Richard Armstrong; Terry Haran; Kyle McDonald; Rick Forster; Kelly Elder

2008-01-01

This paper describes satellite data collected as part of the 2002/03 Cold Land Processes Experiment (CLPX). These data include multispectral and hyperspectral optical imaging, and passive and active microwave observations of the test areas. The CLPX multispectral optical data include the Advanced Very High Resolution Radiometer (AVHRR), the Landsat Thematic Mapper/...

Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

USGS Publications Warehouse

Stow, Douglas A.; Hope, Allen; McGuire, David; Verbyla, David; Gamon, John A.; Huemmrich, Fred; Houston, Stan; Racine, Charles H.; Sturm, Matthew; Tape, Ken D.; Hinzman, Larry D.; Yoshikawa, Kenji; Tweedie, Craig E.; Noyle, Brian; Silapaswan, Cherie; Douglas, David C.; Griffith, Brad; Jia, Gensuo; Howard E. Epstein,; Walker, Donald A.; Daeschner, Scott; Petersen, Aaron; Zhou, Liming; Myneni, Ranga B.

2004-01-01

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land–Air–Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.

Intercomparison of 30+ years of AVHRR and Landsat-5 TM Surface Reflectance using Multiple Pseudo-Invariant Calibration Sites

NASA Astrophysics Data System (ADS)

Santamaría-Artigas, A. E.; Franch, B.; Vermote, E.; Roger, J. C.; Justice, C. O.

2017-12-01

The 30+ years daily surface reflectance long term data record (LTDR) from the Advanced Very High Resolution Radiometer (AVHRR) is a valuable source of information for long-term studies of the Earth surface. This LTDR was generated by combining observations from multiple AVHRR sensors aboard different NOAA satellites starting from the early 1980s, and due to the lack of on-board calibration its quality should be evaluated. Previous studies have used observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) over pseudo-invariant calibration sites (PICS) as a calibrated reference to assess the performance of AVHRR products. However, this limits the evaluation to the period after MODIS launch. In this work, the AVHRR surface reflectance LTDR was evaluated against Landsat-5 Thematic Mapper (TM) data using observations from 4 well known pseudo-invariant calibration sites (i.e. Sonoran, Saharan, Sudan1, and Libya4) over an extended time period (1984-2011). For the intercomparison, AVHRR and TM observations of each site were extracted and averaged over a 20 km x 20 km area and aggregated to monthly mean values. In order to account for the spectral differences between sensors, Hyperion hyperspectral data from the Sonoran and Libya4 sites were convolved with sensor-specific relative spectral responses, and used to compute spectral band adjustment factors (SBAFs). Results of the intercomparison are reported in terms of the root mean square difference (RMSD) and determination coefficient (r2). In general, there is good agreement between the surface reflectance products from both sensors. The overall RMSD and r2 for all the sites and AVHRR/TM combinations were 0.03 and 0.85 for the red band, and 0.04 and 0.81 for the near-infrared band. These results show the strong performance of the AVHRR surface reflectance LTDR through all of the considered period. Thus, remarking its usefulness and value for long term Earth studies. Figure 1 shows the red (filled markers

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

Seasonality and Management Affect Land Surface Temperature Differences Between Loblolly Pine and Switchgrass Ecosystems in Central Virginia

NASA Astrophysics Data System (ADS)

Ahlswede, B.; Thomas, R. Q.; O'Halloran, T. L.; Rady, J.; LeMoine, J.

2017-12-01

Changes in land-use and land management can have biogeochemical and biophysical effects on local and global climate. While managed ecosystems provide known food and fiber benefits, their influence on climate is less well quantified. In the southeastern United States, there are numerous types of intensely managed ecosystems but pine plantations and switchgrass fields represent two biogeochemical and biophysical extremes; a tall, low albedo forest with trees harvested after multiple decades vs. a short, higher albedo C4 grass field that is harvested annually. Despite the wide spread use of these ecosystems for timber and bioenergy, a quantitative, empirical evaluation of the net influence of these ecosystems on climate is lacking because it requires measuring both the greenhouse gas and energy balance of the ecosystems while controlling for the background weather and soil environment. To address this need, we established a pair of eddy flux towers in these ecosystems that are co-located (1.5 km apart) in Central Virginia and measured the radiative energy, non-radiative energy and carbon fluxes, along with associated biometeorology variables; the paired site has run since April 2016. During the first 1.5 years (two growing seasons), we found strong seasonality in the difference in surface temperature between the two ecosystems. In the growing seasons, both sites had similar surface temperature despite higher net radiation in pine. Following harvest of the switchgrass in September, the switchgrass temperatures increased relative to pine. In the winter, the pine ecosystem was warmer. We evaluate the drivers of these intra-annual dynamics and compare the climate influence of these biophysical differences to the differences in carbon fluxes between the sites using a suite of established climate regulation services metrics. Overall, our results show tradeoffs exist between the biogeochemical and biophysical climate services in managed ecosystems in the southeastern United

A 16-year time series of 1 km AVHRR satellite data of the conterminous United States and Alaska

USGS Publications Warehouse

Eidenshink, Jeff

2006-01-01

The U.S. Geological Survey (USGS) has developed a 16-year time series of vegetation condition information for the conterminous United States and Alaska using 1 km Advanced Very High Resolution Radiometer (AVHRR) data. The AVHRR data have been processed using consistent methods that account for radiometric variability due to calibration uncertainty, the effects of the atmosphere on surface radiometric measurements obtained from wide field-of-view observations, and the geometric registration accuracy. The conterminous United States and Alaska data sets have an atmospheric correction for water vapor, ozone, and Rayleigh scattering and include a cloud mask derived using the Clouds from AVHRR (CLAVR) algorithm. In comparison with other AVHRR time series data sets, the conterminous United States and Alaska data are processed using similar techniques. The primary difference is that the conterminous United States and Alaska data are at 1 km resolution, while others are at 8 km resolution. The time series consists of weekly and biweekly maximum normalized difference vegetation index (NDVI) composites.

NDVI, C3 and C4 production, and distributions in Great Plains grassland land cover classes

USGS Publications Warehouse

Tieszen, L.L.; Reed, Bradley C.; Bliss, Norman B.; Wylie, Bruce K.; DeJong, Benjamin D.

1997-01-01

The distributions of C3 and C4 grasses were used to interpret the distribution, seasonal performance, and potential production of grasslands in the Great Plains of North America. Thirteen major grassland seasonal land cover classes were studied with data from three distinct sources. Normalized Difference Vegetation Index (NDVI) data derived from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) sensor were collected for each pixel over a 5-yr period (1989–1993), analyzed for quantitative attributes and seasonal relationships, and then aggregated by land cover class. Data from the State Soil Geographic (STATSGO) database were used to identify dominant plant species contributing to the potential production in each map unit. These species were identified as C3 or C4, and contributions to production were aggregated to provide estimates of the percentage of C3 and C4 production for each intersection of the STATSGO map units and the seasonal land cover classes. Carbon isotope values were obtained at specific sites from the soil organic matter of the upper horizon of soil cores and were related to STATSGO estimates of potential production.The grassland classes were distributed with broad northwest-to-southeast orientations. Some classes had large variations in C3 and C4 composition with high proportions of C4species in the south and low proportions in the north. This diversity of photosynthetic types within land cover classes that cross regions of different temperature and precipitation results in similar seasonal patterns and magnitudes of NDVI. The easternmost class, 65, containing tallgrass prairie components, bluestem, Indiangrass, and switchgrass, possessed the highest maximum NDVI and time-integrated NDVI values each year. Grassland classes varied over 5 yr from a high integrated NDVI mean of 4.9 in class 65 in the east to a low of 1.2 in class 76 (sand sage, blue grama, wheatgrass, and buffalograss) in the

Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II.

PubMed

Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

2010-01-01

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations' carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982-1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

Evolution of Indian land surface biases in the seasonal hindcasts from the Met Office Global Seasonal Forecasting System GloSea5

NASA Astrophysics Data System (ADS)

Chevuturi, Amulya; Turner, Andrew G.; Woolnoug, Steve J.; Martin, Gill

2017-04-01

In this study we investigate the development of biases over the Indian region in summer hindcasts of the UK Met Office coupled initialised global seasonal forecasting system, GloSea5-GC2. Previous work has demonstrated the rapid evolution of strong monsoon circulation biases over India from seasonal forecasts initialised in early May, together with coupled strong easterly wind biases on the equator. These mean state biases lead to strong precipitation errors during the monsoon over the subcontinent. We analyse a set of three springtime start dates for the 20-year hindcast period (1992-2011) and fifteen total ensemble members for each year. We use comparisons with variety of observations to assess the evolution of the mean state biases over the Indian land surface. All biases within the model develop rapidly, particularly surface heat and radiation flux biases. Strong biases are present within the model climatology from pre-monsoon (May) in the surface heat fluxes over India (higher sensible / lower latent heat fluxes) when compared to observed estimates. The early evolution of such biases prior to onset rains suggests possible problems with the land surface scheme or soil moisture errors. Further analysis of soil moisture over the Indian land surface shows a dry bias present from the beginning of the hindcasts during the pre-monsoon. This lasts until the after the monsoon develops (July) after which there is a wet bias over the region. Soil moisture used for initialization of the model also shows a dry bias when compared against the observed estimates, which may lead to the same in the model. The early dry bias in the model may reduce local moisture availability through surface evaporation and thus may possibly limit precipitation recycling. On this premise, we identify and test the sensitivity of the monsoon in the model against higher soil moisture forcing. We run sensitivity experiments initiated using gridpoint-wise annual soil moisture maxima over the Indian

Estimating the effective spatial resolution of an AVHRR time series

USGS Publications Warehouse

Meyer, D.J.

1996-01-01

A method is proposed to estimate the spatial degradation of geometrically rectified AVHRR data resulting from misregistration and off-nadir viewing, and to infer the cumulative effect of these degradations over time. Misregistrations are measured using high resolution imagery as a geometric reference, and pixel sizes are computed directly from satellite zenith angles. The influence or neighbouring features on a nominal 1 km by 1 km pixel over a given site is estimated from the above information, and expressed as a spatial distribution whose spatial frequency response is used to define an effective field-of-view (EFOV) for a time series. In a demonstration of the technique applied to images from the Conterminous U.S. AVHRR data set, an EFOV of 3·1km in the east-west dimension and 19 km in the north-south dimension was estimated for a time series accumulated over a grasslands test site.

Simulating the hydrological impacts of inter-annual and seasonal variability in land use land cover change on streamflow

NASA Astrophysics Data System (ADS)

Taxak, A. K.; Ojha, C. S. P.

2017-12-01

Land use and land cover (LULC) changes within a watershed are recognised as an important factor affecting hydrological processes and water resources. LULC changes continuously not only in long term but also on the inter-annual and season level. Changes in LULC affects the interception, storage and moisture. A widely used approach in rainfall-runoff modelling through Land surface models (LSM)/ hydrological models is to keep LULC same throughout the model running period. In long term simulations where land use change take place during the run period, using a single LULC does not represent a true picture of ground conditions could result in stationarity of model responses. The present work presents a case study in which changes in LULC are incorporated by using multiple LULC layers. LULC for the study period were created using imageries from Landsat series, Sentinal, EO-1 ALI. Distributed, physically based Variable Infiltration Capacity (VIC) model was modified to allow inclusion of LULC as a time varying variable just like climate. The Narayani basin was simulated with LULC, leaf area index (LAI), albedo and climate data for 1992-2015. The results showed that the model simulation with varied parametrization approach has a large improvement over the conventional fixed parametrization approach in terms of long-term water balance. The proposed modelling approach could improve hydrological modelling for applications like land cover change studies, water budget studies etc.

Automated cloud screening of AVHRR imagery using split-and-merge clustering

NASA Technical Reports Server (NTRS)

Gallaudet, Timothy C.; Simpson, James J.

1991-01-01

Previous methods to segment clouds from ocean in AVHRR imagery have shown varying degrees of success, with nighttime approaches being the most limited. An improved method of automatic image segmentation, the principal component transformation split-and-merge clustering (PCTSMC) algorithm, is presented and applied to cloud screening of both nighttime and daytime AVHRR data. The method combines spectral differencing, the principal component transformation, and split-and-merge clustering to sample objectively the natural classes in the data. This segmentation method is then augmented by supervised classification techniques to screen clouds from the imagery. Comparisons with other nighttime methods demonstrate its improved capability in this application. The sensitivity of the method to clustering parameters is presented; the results show that the method is insensitive to the split-and-merge thresholds.

Dependence of NOAA-AVHRR recorded radiance on scan angle, atmospheric turbidity and unresolved cloud

NASA Technical Reports Server (NTRS)

Piwinski, D. J.; Schoch, L. B.; Duggin, M. J.; Whitehead, V.; Ryland, E.

1984-01-01

Experimental evidence on the scan angle and sun angle dependence of radiance recorded by the Advanced Very High Resolution Radiometer (AVHRR) devices on the NOAA-6 and NOAA-7 satellites is presented. The effects of atmospheric turbidity at various scan angles is shown, and simulations of angular anisotropy and recorded radiance are compared with the recorded digital data from the AVHRR obtained over the Great Plains area of the US. Evidence is presented on the effects of unresolved cloud on the recorded radiance and vegetative indices from uniform, vegetative targets.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Dry season distribution of land crabs, Gecarcinus quadratus (Crustacea: Gecarcinidae), in Corcovado National Park, Costa Rica.

PubMed

Griffiths, Megan E; Mohammad, Basma A; Vega, Andres

2007-03-01

The land crab Gecarcinus quadratus is an engineering species that controls nutrient cycling in tropical forests. Factors regulating their coastal distribution are not fully understood. We quantified land crab distribution during the dry season at Sirena Field Station in Corcovado National Park, Costa Rica, and found that land crab burrow density decreases with increasing distance from the ocean. Leaf litter depth and tree seedling density are negatively correlated with land crab burrow density. Burrows are strongly associated with sand substrate and burrow density is comparatively low in clay substrate. Results suggest that G. quadratus is limited to a narrow coastal zone with sand substrate, and this distribution could have profound effects on plant community structure.

Differences in visible and near-IR responses, and derived vegetation indices, for the NOAA-9 and NOAA-10 AVHRRs: a case study

USGS Publications Warehouse

Gallo, Kevin P.; Eidenshink, Jeffery C.

1988-01-01

This study evaluates the differences in the visible and near-IR responses of the Advanced Very High Resolution Radiometers (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)-9 and -10 satellites for coincident sample locations. The study also evaluates the differences in vegetation indices computed from those data. Data were acquired of the southeast portion of the United States for the 6 December 1986 daylight orbits of NOAA-9 and NOAA-10 satellites. The results suggest that, with appropriate gain and offset, the vegetation indices of the two sensor systems may be interchangeable for assessment of land surfaces.

Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

PubMed Central

Alcaraz-Segura, Domingo; Liras, Elisa; Tabik, Siham; Paruelo, José; Cabello, Javier

2010-01-01

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast. PMID:22205868

Winter wheat production forecast in United States of America using AVHRR historical data and NCAR Growing Degree Day

NASA Astrophysics Data System (ADS)

Claverie, M.; Franch, B.; Vermote, E.; Becker-Reshef, I.; Justice, C. O.

2015-12-01

Wheat is one of the key cereals crop grown worldwide. Thus, accurate and timely forecasts of its production are critical for informing agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) used an empirical generalized model for forecasting winter wheat production using combined BRDF-corrected daily surface reflectance from the Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop type masks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel, and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. Recently, Franch et al. (2015) included Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts between a month to a month and a half prior to the peak NDVI (i.e. 1-2.5 months prior to harvest), while conserving the accuracy of the original model. In this study, we apply these methods to historical data from the Advanced Very High Resolution Radiometer (AVHRR). We apply both the original and the modified model to United States of America from 1990 to 2014 and inter-compare the AVHRR results to MODIS from 2000 to 2014.

Wet-dry seasonal and vertical geochemical variations in soil water and their driving forces under different land covers in southwest China karst

NASA Astrophysics Data System (ADS)

Wang, Peng; Hu, Bill X.; Wu, Chuanhao; Xu, Kai

2017-04-01

Karst aquifers supply drinking water for 25% of the world's population, and they are, however, vulnerable to climate change. Bimonthly hydrochemical data in karst soil water samples from July 2010 to July 2011 were obtained to reveal the seasonal and vertical geochemical variations in soil water under five vegetation types in Qingmuguan, a small karst catchment in southwest China. Soil water chemistry was dominated by Ca2+, HCO3-, and SO42- because of the dissolution of limestone, dolomite, and gypsum minerals in the strata. The predominant hydrochemical types in soil water were Ca2+-HCO3-, Ca2+-SO42-, and mixed Ca2+-HCO3-SO42-. Ca2+ and HCO3- concentrations ranked in the following order: shrub land > dry land > afforestation farmland > bamboo land > grassland. In warm and wet seasons, the main ion concentrations in soil water from grasslands were low. Na+, K+, Ca2+, Mg2+, HCO3-, SO42-, and Cl- concentrations in soil water from other lands were high. An opposite trend was observed in cold and dry seasons. Marked seasonal variations were observed in Ca2+, HCO3-, and NO3- in soil water from dry land. The main ion concentrations in soil water from bamboo lands decreased as soil depth increased. By contrast, the chemistry of soil water from other lands increased as soil depth increased. Their ions were accumulated in depth. A consistent high and low variation between the main ions in soil water and the contents of carbonate and CO2 was found in the soil. Hydrochemical changes in soil water were regulated by the effects of dilution and soil CO2.

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Seasonal temperature responses to land-use change in the western United States

USGS Publications Warehouse

Kueppers, L.M.; Snyder, M.A.; Sloan, L.C.; Cayan, D.; Jin, J.; Kanamaru, H.; Kanamitsu, M.; Miller, N.L.; Tyree, Mary; Du, H.; Weare, B.

2008-01-01

In the western United States, more than 79 000??km2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) - RSM, RegCM3, MM5-CLM3, and DRCM - to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (- 1.4 to - 3.1????C) and maximum (- 2.9 to - 6.1????C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest. ?? 2007 Elsevier B.V. All rights reserved.

Assessing land cover performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis

USGS Publications Warehouse

Budde, M.E.; Tappan, G.; Rowland, James; Lewis, J.; Tieszen, L.L.

2004-01-01

The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.

Land Surface Phenologies and Seasonalities of Croplands and Grasslands in the US Prairie Pothole Region Using Passive Microwave Data (2003-2015)

NASA Astrophysics Data System (ADS)

Alemu, W. G.; Henebry, G. M.

2017-12-01

Grasslands and wetlands in the Prairie Pothole Region (PPR) have been converted to croplands in recent years. Crops cultivated in the PPR are also changing: spring wheat and alfalfa/hay are being switched to corn and soybean due to biofuel demand. According to the USDA Cropland Data Layer (CDL) from 2003 to 2015, spring wheat significantly decreased (r2 = 0.74), while corn and soybeans significantly increased (r2 = 0.86). We characterized land surface phenologies and land surface seasonalities across the PPR using the finer temporal (twice daily) but much lower spatial (25 km) resolution Advanced Microwave Scanning Radiometer (AMSR: blended from AMSR-E and AMSR2) enhanced land surface parameters for 2003-2015 (DOY 91-330 annual cycles). We tracked the temporal development of these land surface parameters as a function of accumulated growing degree-days (AGDD) based on the AMSR retrieved air temperature data. Growing degree-days (GDD) revealed distinct seasonality typical to temperate grasslands and croplands. GDD peaks were 23°C and it peaks at 1700°C AGDD. Precipitable water vapor (V) displayed seasonality comparable to GDD. Vegetation optical depth (VOD) revealed distinct land surface phenologies for grasslands versus croplands. We explored the changing crop fractions within the 25 km AMSR pixels using the CDL. Crop-dominated sites VOD time series caught the early spring growth, ploughing, and crop growth dynamics. In contrast, the VOD time series at grass-dominated sites exhibited a lower but more extended amplitude throughout the non-frozen season. VODs peaked at 1.6 and 1.3 for croplands and grasslands, respectively. Croplands peaked about a month later than grasslands (2200 °C AGDD vs. 1600 °C AGDD). The other parameters available from the AMSR dataset—soil moisture (sm), and fractional open water (fw)—together with the AGDD time series constructed from the AMSR air temperature data revealed the passage of storm systems during the growing season. Soil

Trends in LST over the peninsular Spain as derived from the AVHRR imagery data

NASA Astrophysics Data System (ADS)

Khorchani, Makki; Vicente-Serrano, Sergio M.; Azorin-Molina, Cesar; Garcia, Monica; Martin-Hernandez, Natalia; Peña-Gallardo, Marina; El Kenawy, Ahmed; Domínguez-Castro, Fernando

2018-07-01

This study analyzes the spatio-temporal variability and trends of land surface temperature (LST) over peninsular Spain, considering all the available historical satellite imagery data from the NOAA-AVHRR product from July 1981 to June 2015 and explores whether changes in LST are related to the observed changes in air temperature, solar radiation and land cover. We found that LST showed a significant increase between 1982 and 2014, with an average increase on the order of 0.71 °C decade-1, being stronger during summertime (1.53 °C decade-1). The results also indicate a strong spatial coherence between LST and NDVI changes. The areas that experienced an increase in the LST were spatially consistent with those areas with no changes or even a dominant decrease in vegetation coverage. In addition, the strong increase of LST is coherent with observations of the recent radiative forcing affecting Spain, particularly during summertime. The confidence of the obtained LST trends during summer is also reinforced by the spatial differences recorded in trends, in addition to the differences found between land cover types. Specifically, the magnitude of this increase was much higher in the dryland non-permanent agricultural areas, which are usually harvested during summer, when soil is dominantly nude. In contrast, in well-developed forests, the magnitude of LST was much lower. Our results on the observed LST trends and their spatial patterns can contribute to better understanding of the recent eco-hydrological processes in peninsular Spain.

Estimating the beam attenuation coefficient in coastal waters from AVHRR imagery

NASA Astrophysics Data System (ADS)

Gould, Richard W.; Arnone, Robert A.

1997-09-01

This paper presents an algorithm to estimate particle beam attenuation at 660 nm ( cp660) in coastal areas using the red and near-infrared channels of the NOAA AVHRR satellite sensor. In situ reflectance spectra and cp660 measurements were collected at 23 stations in Case I and II waters during an April 1993 cruise in the northern Gulf of Mexico. The reflectance spectra were weighted by the spectral response of the AVHRR sensor and integrated over the channel 1 waveband to estimate the atmospherically corrected signal recorded by the satellite. An empirical relationship between integrated reflectance and cp660 values was derived with a linear correlation coefficient of 0.88. Because the AVHRR sensor requires a strong channel 1 signal, the algorithm is applicable in highly turbid areas ( cp660 > 1.5 m -1) where scattering from suspended sediment strongly controls the shape and magnitude of the red (550-650 nm) reflectance spectrum. The algorithm was tested on a data set collected 2 years later in different coastal waters in the northern Gulf of Mexico and satellite estimates of cp660 averaged within 37% of measured values. Application of the algorithm provides daily images of nearshore regions at 1 km resolution for evaluating processes affecting ocean color distribution patterns (tides, winds, currents, river discharge). Further validation and refinement of the algorithm are in progress to permit quantitative application in other coastal areas. Published by Elsevier Science Ltd

Seasonal Dynamics of Water Use Strategy of Two Salix Shrubs in Alpine Sandy Land, Tibetan Plateau.

PubMed

Zhu, Yajuan; Wang, Guojie; Li, Renqiang

2016-01-01

Water is a limiting factor for plant growth and vegetation dynamics in alpine sandy land of the Tibetan Plateau, especially with the increasing frequency of extreme precipitation events and drought caused by climate change. Therefore, a relatively stable water source from either deeper soil profiles or ground water is necessary for plant growth. Understanding the water use strategy of dominant species in the alpine sandy land ecosystem is important for vegetative rehabilitation and ecological restoration. The stable isotope methodology of δD, δ18O, and δ13C was used to determine main water source and long-term water use efficiency of Salix psammophila and S. cheilophila, two dominant shrubs on interdune of alpine sandy land in northeastern Tibetan Plateau. The root systems of two Salix shrubs were investigated to determine their distribution pattern. The results showed that S. psammophila and S. cheilophila absorbed soil water at different soil depths or ground water in different seasons, depending on water availability and water use strategy. Salix psammophila used ground water during the growing season and relied on shallow soil water recharged by rain in summer. Salix cheilophila used ground water in spring and summer, but relied on shallow soil water recharged by rain in spring and deep soil water recharged by ground water in fall. The two shrubs had dimorphic root systems, which is coincident with their water use strategy. Higher biomass of fine roots in S. psammophila and longer fine roots in S. cheilophila facilitated to absorb water in deeper soil layers. The long-term water use efficiency of two Salix shrubs increased during the dry season in spring. The long-term water use efficiency was higher in S. psammophila than in S. cheilophila, as the former species is better adapted to semiarid climate of alpine sandy land.

Seasonal Dynamics of Water Use Strategy of Two Salix Shrubs in Alpine Sandy Land, Tibetan Plateau

PubMed Central

Zhu, Yajuan; Wang, Guojie; Li, Renqiang

2016-01-01

Water is a limiting factor for plant growth and vegetation dynamics in alpine sandy land of the Tibetan Plateau, especially with the increasing frequency of extreme precipitation events and drought caused by climate change. Therefore, a relatively stable water source from either deeper soil profiles or ground water is necessary for plant growth. Understanding the water use strategy of dominant species in the alpine sandy land ecosystem is important for vegetative rehabilitation and ecological restoration. The stable isotope methodology of δD, δ18O, and δ13C was used to determine main water source and long-term water use efficiency of Salix psammophila and S. cheilophila, two dominant shrubs on interdune of alpine sandy land in northeastern Tibetan Plateau. The root systems of two Salix shrubs were investigated to determine their distribution pattern. The results showed that S. psammophila and S. cheilophila absorbed soil water at different soil depths or ground water in different seasons, depending on water availability and water use strategy. Salix psammophila used ground water during the growing season and relied on shallow soil water recharged by rain in summer. Salix cheilophila used ground water in spring and summer, but relied on shallow soil water recharged by rain in spring and deep soil water recharged by ground water in fall. The two shrubs had dimorphic root systems, which is coincident with their water use strategy. Higher biomass of fine roots in S. psammophila and longer fine roots in S. cheilophila facilitated to absorb water in deeper soil layers. The long-term water use efficiency of two Salix shrubs increased during the dry season in spring. The long-term water use efficiency was higher in S. psammophila than in S. cheilophila, as the former species is better adapted to semiarid climate of alpine sandy land. PMID:27243772

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987-2016) case study of Hamoun Wetland, Iran.

PubMed

Kharazmi, Rasoul; Tavili, Ali; Rahdari, Mohammad Reza; Chaban, Lyudmila; Panidi, Evgeny; Rodrigo-Comino, Jesús

2018-05-23

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987-2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R 2  = 0.94) than fall and spring (R 2  = 0.58) seasons. Before 2000, ~ 50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun

Microwave Brightness Of Land Surfaces From Outer Space

NASA Technical Reports Server (NTRS)

Kerr, Yann H.; Njoku, Eni G.

1991-01-01

Mathematical model approximates microwave radiation emitted by land surfaces traveling to microwave radiometer in outer space. Applied to measurements made by Scanning Multichannel Microwave Radiometer (SMMR). Developed for interpretation of microwave imagery of Earth to obtain distributions of various chemical, physical, and biological characteristics across its surface. Intended primarily for use in mapping moisture content of soil and fraction of Earth covered by vegetation. Advanced Very-High-Resolution Radiometer (AVHRR), provides additional information on vegetative cover, thereby making possible retrieval of soil-moisture values from SMMR measurements. Possible to monitor changes of land surface during intervals of 5 to 10 years, providing significant data for mathematical models of evolution of climate.

Hydrologic impacts of land cover variability and change at seasonal to decadal time scales over North America, 1992-2016

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2017-12-01

Land cover variability and change have been shown to influence the terrestrial hydrologic cycle by altering the partitioning of moisture and energy fluxes. However, the magnitude and directionality of the relationship between land cover and surface hydrology has been shown to vary substantially across regions. Here, we provide an assessment of the impacts of land cover change on hydrologic processes at seasonal (vegetation phenology) to decadal scales (land cover conversion) in the United States and Mexico. To this end, we combine time series of remotely-sensed land surface characteristics with land cover maps for different decades as input to the Variable Infiltration Capacity hydrologic model. Land surface characteristics (leaf area index, surface albedo, and canopy fraction derived from normalized difference vegetation index) were obtained from the Moderate Resolution Imaging Spectrometer (MODIS) at 8-day intervals over the period 2000-2016. Land cover maps representing conditions in 1992, 2001, and 2011 were derived by homogenizing the National Land Cover Database over the US and the INEGI Series I through V maps over Mexico. An additional map covering all of North America was derived from the most frequent land cover class observed in each pixel of the MODIS MOD12Q1 product during 2001-2013. Land surface characteristics were summarized over land cover fractions at 1/16 degree (6 km) resolution. For each land cover map, hydrologic simulations were conducted that covered the period 1980-2013, using the best-available, hourly meteorological forcings at a similar spatial resolution. Based on these simulations, we present a comparison of the contributions of land cover change and climate variability at seasonal to decadal scales on the hydrologic and energy budgets, identifying the dominant components through time and space. This work also offers a valuable dataset on land cover variability and its hydrologic response for continental-scale assessments and modeling.

Analysis of AVHRR, CZCS and historical in situ data off the Oregon Coast

NASA Technical Reports Server (NTRS)

Strub, P. Ted; Chelton, Dudley B.

1990-01-01

The original scientific objectives of this grant were to: (1) characterize the seasonal cycles and interannual variability for phytoplankton concentrations and sea surface temperature (SST) in the California Current using satellite data; and (2) to explore the spatial and temporal relationship between these variables and surface wind forcing. An additional methodological objective was to develop statistical methods for forming mean fields, which minimize the effects of random data gaps and errors in the irregularly sampled CZCS (Coastal Zone Color Scanner) and AVHRR (Advanced Very High Resolution Radiometer) satellite data. A final task was to evaluate the level of uncertainty in the wind fields used for the statistical analysis. Funding in the first year included part of the cost of an image processing system to enable this and other projects to process and analyze satellite data. This report consists of summaries of the major projects carried out with all or partial support from this grant. The appendices include a list of papers and professional presentations supported by the grant, as well as reprints of the major papers and reports.

Water quality of small seasonal wetlands in the Piedmont ecoregion, South Carolina, USA: Effects of land use and hydrological connectivity.

PubMed

Yu, Xubiao; Hawley-Howard, Joanna; Pitt, Amber L; Wang, Jun-Jian; Baldwin, Robert F; Chow, Alex T

2015-04-15

Small, shallow, seasonal wetlands with short hydroperiod (2-4 months) play an important role in the entrapment of organic matter and nutrients and, due to their wide distribution, in determining the water quality of watersheds. In order to explain the temporal, spatial and compositional variation of water quality of seasonal wetlands, we collected water quality data from forty seasonal wetlands in the lower Blue Ridge and upper Piedmont ecoregions of South Carolina, USA during the wet season of February to April 2011. Results indicated that the surficial hydrological connectivity and surrounding land-use were two key factors controlling variation in dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) in these seasonal wetlands. In the sites without obvious land use changes (average developed area <0.1%), the DOC (p < 0.001, t-test) and TDN (p < 0.05, t-test) of isolated wetlands were significantly higher than that of connected wetlands. However, this phenomenon can be reversed as a result of land use changes. The connected wetlands in more urbanized areas (average developed area = 12.3%) showed higher concentrations of dissolved organic matter (DOM) (DOC: 11.76 ± 6.09 mg L(-1), TDN: 0.74 ± 0.22 mg L(-1), mean ± standard error) compared to those in isolated wetlands (DOC: 7.20 ± 0.62 mg L(-1), TDN: 0.20 ± 0.08 mg L(-1)). The optical parameters derived from UV and fluorescence also confirmed significant portions of protein-like fractions likely originating from land use changes such as wastewater treatment and livestock pastures. The average of C/N molar ratios of all the wetlands decreased from 77.82 ± 6.72 (mean ± standard error) in February to 15.14 ± 1.58 in April, indicating that the decomposition of organic matter increased with the temperature. Results of this study demonstrate that the water quality of small, seasonal wetlands has a direct and close association with the surrounding environment. Copyright © 2015 Elsevier Ltd. All rights

Time series decomposition of remotely sensed land surface temperature and investigation of trends and seasonal variations in surface urban heat islands

NASA Astrophysics Data System (ADS)

Quan, Jinling; Zhan, Wenfeng; Chen, Yunhao; Wang, Mengjie; Wang, Jinfei

2016-03-01

Previous time series methods have difficulties in simultaneous characterization of seasonal, gradual, and abrupt changes of remotely sensed land surface temperature (LST). This study proposed a model to decompose LST time series into trend, seasonal, and noise components. The trend component indicates long-term climate change and land development and is described as a piecewise linear function with iterative breakpoint detection. The seasonal component illustrates annual insolation variations and is modeled as a sinusoidal function on the detrended data. This model is able to separate the seasonal variation in LST from the long-term (including gradual and abrupt) change. Model application to nighttime Moderate Resolution Imaging Spectroradiometer (MODIS)/LST time series during 2000-2012 over Beijing yielded an overall root-mean-square error of 1.62 K between the combination of the decomposed trend and seasonal components and the actual MODIS/LSTs. LST decreased (~ -0.086 K/yr, p < 0.1) in 53% of the study area, whereas it increased with breakpoints in 2009 (~0.084 K/yr before and ~0.245 K/yr after 2009) between the fifth and sixth ring roads. The decreasing trend was stronger over croplands than over urban lands (p < 0.05), resulting in an increasing trend in surface urban heat island intensity (SUHII, 0.022 ± 0.006 K/yr). This was mainly attributed to the trends in urban-rural differences in rainfall and albedo. The SUHII demonstrated a concave seasonal variation primarily due to the seasonal variations of urban-rural differences in temperature cooling rate (related to canyon structure, vegetation, and soil moisture) and surface heat dissipation (affected by humidity and wind).

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1994-01-01

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

[Analysis on the relationship between malaria epidemics and NOAA-AVHRR NDVI in Hainan province].

PubMed

Wen, Liang; Xu, De-zhong; Wang, Shan-qing; Li, Cai-xu; Zhang, Zhi-ying; Su, Yong-qiang

2005-04-01

To explore the relationship between malaria epidemics and NOAA-AVHRR NDVI. Data on malaria were collected in all 19 counties in Hainan province from Feb, 1995 to Jan, 1996. Values regarding normalized difference vegetation index (NDVI)-related indicators including mean and maximum values of NDVI, the area proportion of NDVI values of 145- and 145+, months with NDVI values of 135+, 140+, 145+, 150+ of these counties in this period were all extracted from NOAA-AVHRR images, using ERDAS8.5 software. The coefficients of correlation of malaria incidences and these NDVI-related indicator values were then calculated with SPSS 11.0. The incidence of malaria showed positive correlations to mean and maximum values of NDVI, the area proportion of NDVI values of 145+ and months with NDVI values of 135+, 140+, 145+, 150+ respectively, but having negative correlation to the area of NDVI values of 145-. The malaria epidemic regions were in accordance with those regions that the NDVI values of 145+ were continuing for 9 months or more. Malaria prevalence was associated with NOAA-AVHRR NDVI value which could be considered to be use for malaria surveillance in Hainan province.

Knowing your neighbourhood—the effects of Epichloë endophytes on foliar fungal assemblages in perennial ryegrass in dependence of season and land-use intensity

PubMed Central

Guerreiro, Marco Alexandre; Peršoh, Derek; Begerow, Dominik; Krauss, Jochen

2018-01-01

Epichloë endophytes associated with cool-season grass species can protect their hosts from herbivory and can suppress mycorrhizal colonization of the hosts’ roots. However, little is known about whether or not Epichloë endophyte infection can also change the foliar fungal assemblages of the host. We tested 52 grassland study sites along a land-use intensity gradient in three study regions over two seasons (spring vs. summer) to determine whether Epichloë infection of the host grass Lolium perenne changes the fungal community structure in leaves. Foliar fungal communities were assessed by Next Generation Sequencing of the ITS rRNA gene region. Fungal community structure was strongly affected by study region and season in our study, while land-use intensity and infection with Epichloë endophytes had no significant effects. We conclude that effects on non-systemic endophytes resulting from land use practices and Epichloë infection reported in other studies were masked by local and seasonal variability in this study’s grassland sites. PMID:29780665

Trend analysis of time-series phenology of North America derived from satellite data

USGS Publications Warehouse

Reed, B.C.

2006-01-01

Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface since the 1980s. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land-surface processes over large areas. Phenologic metrics, including start of season, end of season, duration of season, and seasonally integrated greenness, were derived from 8 km advanced very high resolution radiometer (AVHRR) data over North America spanning the years 1982-2003. Trend analysis was performed on annual summaries of the metrics to determine areas with increasing or decreasing growing season trends for the time period under study. Results show a trend toward earlier starts of season in limited areas of the mixed boreal forest, and a trend toward later end of season in well-defined areas of New England and southeastern Canada. Results in Saskatchewan, Canada, include a trend toward longer duration of season over a well-defined area, principally as a result of regional changes in land use practices. Changing seasonality appears to be an integrated response to a complex of factors, including climate change, but also, in many places, changes in land use practices. Copyright ?? 2006 by V. H. Winston & Son, Inc. All rights reserved.

Forest mapping of Central America and Mexico with AVHRR data

Treesearch

Keith B. Lannom

2001-01-01

Concerns over changes in global forest resource distributions have prompted a number of studies to examine and map forest areas at continental scales with various types of satillite data. The work described here details the use of Advanced Very High Resolution Radiometer (AVHRR) data in concert with Landsat Thematic Mapper (TM) and Systeme Probatoire d'...

The Calibration of AVHRR/3 Visible Dual Gain Using Meteosat-8 as a MODIS Calibration Transfer Medium

NASA Technical Reports Server (NTRS)

Avey, Lance; Garber, Donald; Nguyen, Louis; Minnis, Patrick

2007-01-01

This viewgraph presentation reviews the NOAA-17 AVHRR visible channels calibrated against MET-8/MODIS using dual gain regression methods. The topics include: 1) Motivation; 2) Methodology; 3) Dual Gain Regression Methods; 4) Examples of Regression methods; 5) AVHRR/3 Regression Strategy; 6) Cross-Calibration Method; 7) Spectral Response Functions; 8) MET8/NOAA-17; 9) Example of gain ratio adjustment; 10) Effect of mixed low/high count FOV; 11) Monitor dual gains over time; and 12) Conclusions

Seasonal use of conservation reserve program lands by white-tailed deer in east-central South Dakota

USGS Publications Warehouse

Gould, Jeffrey H.; Jenkins, Kurt J.

1993-01-01

The Conservation Reserve Program (CRP_, a provision of the 1985 Food Security Act, subsidizes landowners to take highly erodible lands out of cultivation and seed them to perennial cover for 10years. In eastern South Dakota, 0.5 million ha were enrolled in the CRP from 1985 to 1990 (Agric. Stabilization and Conserv. Serv., Brookings, S.D., unpubl. Data), which represents the largest change in conservation land-use practices in the region since the 1956 Soil Bank Program (Goetz 1987).Although the CRP is anticipated to produce substantial benefits for some wildlife species, particularly ground-nesting birds, its significance to white-tailed deer (Odocoileus virginianus) in the northern Great Plains agricultural region is poorly understood. Higgins et al. (1987) speculated that proliferation of CRP grasslands may provide a missing habitat component in intensively managed farmland, thereby enhancing several species of wildlife, including white-tailed deer. Deer managers in the region have expressed concerns that improved cover associated with DRP plantings on private land could attract deer and reduce hunter success rates or lead to increased depredation of adjacent croplands or stored winter forages (L. Rice, S.D. Dep. Game, Fish, and Parks, Rapid City, pers. comm., 1989). Our objectives were to describe variation in deer use of CRP lands by season, diel period, and deer activity class as a means of assessing seasonal importance of CRP fields to white-tailed deer in agricultural Midwest.

Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data. [Normalized Difference Vegetation Index

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna R.; Running, Steven W.

1989-01-01

Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. The hypothesis that the relationship between surface temperature and canopy density is sensitivite to seasonal changes in canopy resistance of conifer forests is presently tested. Surface temperature and canopy density were computed for a 20 x 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance for the same period. For all eight days, surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index, implying that latent heat exchange is the major cause of spatial variations in surface radiant tmeperatures.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example

The decreasing range between dry- and wet- season precipitation over land and its effect on vegetation primary productivity.

PubMed

Murray-Tortarolo, Guillermo; Jaramillo, Víctor J; Maass, Manuel; Friedlingstein, Pierre; Sitch, Stephen

2017-01-01

One consequence of climate change is the alteration of global water fluxes, both in amount and seasonality. As a result, the seasonal difference between dry- (p < 100 mm/month) and wet-season (p > 100 mm/month) precipitation (p) has increased over land during recent decades (1980-2005). However, our analysis expanding to a 60-year period (1950-2009) showed the opposite trend. This is, dry-season precipitation increased steadily, while wet-season precipitation remained constant, leading to reduced seasonality at a global scale. The decrease in seasonality was not due to a change in dry-season length, but in precipitation rate; thus, the dry season is on average becoming wetter without changes in length. Regionally, wet- and dry-season precipitations are of opposite sign, causing a decrease in the seasonal variation of the precipitation over 62% of the terrestrial ecosystems. Furthermore, we found a high correlation (r = 0.62) between the change in dry-season precipitation and the trend in modelled net primary productivity (NPP), which is explained based on different ecological mechanisms. This trend is not found with wet-season precipitation (r = 0.04), These results build on the argument that seasonal water availability has changed over the course of the last six decades and that the dry-season precipitation is a key driver of vegetation productivity at the global scale.

The decreasing range between dry- and wet- season precipitation over land and its effect on vegetation primary productivity

PubMed Central

2017-01-01

One consequence of climate change is the alteration of global water fluxes, both in amount and seasonality. As a result, the seasonal difference between dry- (p < 100 mm/month) and wet-season (p > 100 mm/month) precipitation (p) has increased over land during recent decades (1980–2005). However, our analysis expanding to a 60-year period (1950–2009) showed the opposite trend. This is, dry-season precipitation increased steadily, while wet-season precipitation remained constant, leading to reduced seasonality at a global scale. The decrease in seasonality was not due to a change in dry-season length, but in precipitation rate; thus, the dry season is on average becoming wetter without changes in length. Regionally, wet- and dry-season precipitations are of opposite sign, causing a decrease in the seasonal variation of the precipitation over 62% of the terrestrial ecosystems. Furthermore, we found a high correlation (r = 0.62) between the change in dry-season precipitation and the trend in modelled net primary productivity (NPP), which is explained based on different ecological mechanisms. This trend is not found with wet-season precipitation (r = 0.04), These results build on the argument that seasonal water availability has changed over the course of the last six decades and that the dry-season precipitation is a key driver of vegetation productivity at the global scale. PMID:29284050

Introducing Real-Time AVHRR-APT Satellite Imagery in the Classroom Environment

ERIC Educational Resources Information Center

Moxey, Lucas; Tucker, Compton; Sloan, Jim; Chadwick, John

2004-01-01

A low-cost (US$350) satellite receiving station was assembled and operated within a classroom environment in Gainesville (Florida) on October 2001 for acquiring satellite data directly from the Advanced Very High Resolution Radiometer (AVHRR) satellites. The simplicity of the satellite signal makes this source of real-time satellite data readily…

Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

Treesearch

Cynthia S. A. Wallace; Miguel Villarreal; Charles van Riper

2013-01-01

We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using...

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

NASA Astrophysics Data System (ADS)

Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer

2017-11-01

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the

25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 1 2012-04-01 2011-04-01 true Can the number of animals and/or season of use be modified... WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or season... on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified on...

Characterizing Impacts of Land Grabbing on Terrestrial Vegetation and Ecohydrologic change in Mozambique through Multiple-sensor Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Flores, A. N.; Lakshmi, V.; Al-Barakat, R.; Maksimowicz, M.

2017-12-01

Land grabbing, the acquisition of large areas of land by external entities, results from interactions of complex global economic, social, and political processes. These transactions are controversial because they can result in large-scale disruptions to historical land uses, including increased intensity of agricultural practices and significant conversions in land cover. These large-scale disruptions have the potential to impact surface water and energy balance because vegetation controls the partitioning of incoming energy into latent and sensible heat fluxes and precipitation into runoff and infiltration. Because large-scale land acquisitions can impact local ecosystem services, it is important to document changes in terrestrial vegetation associated with these acquisitions to support the assessment of associated impacts on regional surface water and energy balance, spatiotemporal scales of those changes, and interactions and feedbacks with other processes, particularly in the atmosphere. We use remote sensing data from multiple satellite platforms to diagnose and characterize changes in terrestrial vegetation and ecohydrology in Mozambique during periods that bracket periods associated with significant. The Advanced very High Resolution Radiometer (AVHRR) sensor provides long-term continuous data that can document historical seasonal cycles of vegetation greenness. These data are augmented with analyses from Landsat multispectral data, which provides significantly higher spatial resolution. Here we quantify spatiotemporal changes in vegetation are associated with periods of significant land acquisitions in Mozambique. This analysis complements a suite of land-atmosphere modeling experiments designed to deduce potential changes in land surface water and energy budgets associated with these acquisitions. This work advance understanding of how telecouplings between global economic and political forcings and regional hydrology and climate.

Seasonally different response of photosynthetic activity to daytime and night-time warming in the Northern Hemisphere

DOE PAGES

Tan, Jianguang; Piao, Shilong; Chen, Anping; ...

2014-08-27

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night-time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in themore » response of NDVI to changes in day- versus night-time temperatures. For instance, while higher daytime temperature (T max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10 6 km 2) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T max, increases in T max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night-time temperature (T min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day- and night-time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Lastly, understanding the seasonally different responses of vegetation photosynthetic activity to

Assessing phenological change in China from 1982 to 2006 using AVHRR imagery

USDA-ARS?s Scientific Manuscript database

Long term trends in vegetation phenology indicate ecosystem change due to the combined impacts of human activities and climate. In this study, we used 1982 to 2006 Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) imagery across China and the TIMESAT progra...

Validation of national land-cover characteristics data for regional water-quality assessment

USGS Publications Warehouse

Zelt, Ronald B.; Brown, Jesslyn F.; Kelley, M.S.

1995-01-01

Land-cover information is used routinely to support the interpretation of water-quality data. The Prototype 1990 Conterminous US Land Cover Characteristics Data Set, developed primarily from Advanced Very High Resolution Radiometer (AVHRR) data, was made available to the US Geological Survey's National Water-Quality Assessment (NAWQA) Program. The study described in this paper explored the utility of the 1990 national data set for developing quantitative estimates of the areal extent of principal land-cover types within large areal units. Land-cover data were collected in 1993 at 210 sites in the Central Nebraska Basins, one of the NAWQA study units. Median percentage-corn estimates for each sampling stratum wre used to produce areally weighted estimates of the percentage-corn cover for hydrologic units. Comparison of those areal estimates with an independent source of 1992 land-cover data showed good agreement. -Authors

Cropland land surface phenology and seasonality in East Africa: Ethiopia, Tanzania, and South Sudan

NASA Astrophysics Data System (ADS)

Alemu, W. G.; Henebry, G. M.

2015-12-01

Most people in East Africa depend on rainfed agriculture. Rainfall in the region has been decreasing recently and is highly variable in space and time leading to high food insecurity. A comprehensive understanding of the regional cropland dynamics is therefore needed. Land surface phenology and land surface seasonality have important roles in monitoring cropland dynamics in a region with sparse coverage of in situ climatic and biophysical observations. However, commonly used optical satellite data are often degraded by cloud cover, aerosols, and dust and they are restricted to daytime observations. Here we used near-daily passive microwave (PM) data at 25 km spatial resolution from a series of microwave radiometers—AMSR-E, FengYun3B/MWRI, AMSR2—to study cropland dynamics for 2003-2013 in three important grain production areas of East Africa: Ethiopia, Tanzania, and South Sudan. PM data can be collected through clouds and at night. Based on Google Earth imagery, we identified several cropland areas corresponding to PM grid cells. Rainfall from TRMM and atmospheric water vapor (V) from PM data displayed temporal patterns that were unimodal in Ethiopia and South Sudan, but bimodal in Tanzania. We fitted convex quadratic models to link growing season increments of V and vegetation optical depth (VOD) to accumulated V (AV). The models yielded high coefficients of determination (r2 ≥0.8) and phenometrics calculated from the parameter coefficients. Peak rainfall lagged peak V, but preceded peak VOD. Growing degree-days (GDD), calculated from the PM air temperature data, displayed a weaker bimodal seasonality in which the lowest values occurred during the peak rainy season, due to the cooling effect of latent heat flux and coupled with higher reflection of insolation by the cloud deck. V as a function of GDD displays quasi-periodic behavior. Drier sites in the region displayed larger (smaller) intra-annual dynamic range of V (GDD) compared to the moister sites.

Land-atmosphere coupling manifested in warm-season observations on the U.S. southern great plains

DOE PAGES

Phillips, Thomas J.; Klein, Stephen A.

2014-01-28

This study examines several observational aspects of land-atmosphere coupling on daily average time scales during warm seasons of the years 1997 to 2008 at the Department of Energy Atmospheric Radiation Measurement Program’s Southern Great Plains (SGP) Central Facility site near Lamont, Oklahoma. Characteristics of the local land-atmosphere coupling are inferred by analyzing the covariability of selected land and atmospheric variables that include precipitation and soil moisture, surface air temperature, relative humidity, radiant and turbulent fluxes, as well as low-level cloud base height and fractional coverage. For both the energetic and hydrological aspects of this coupling, it is found that large-scalemore » atmospheric forcings predominate, with local feedbacks of the land on the atmosphere being comparatively small much of the time. The weak land feedbacks are manifested by 1) the inability of soil moisture to comprehensively impact the coupled land-atmosphere energetics, and 2) the limited recycling of local surface moisture under conditions where most of the rainfall derives from convective cells that originate at remote locations. There is some evidence, nevertheless, of the local land feedback becoming stronger as the soil dries out in the aftermath of precipitation events, or on days when the local boundary-layer clouds are influenced by thermal updrafts known to be associated with convection originating at the surface. Finally, we also discuss potential implications of these results for climate-model representation of regional land-atmosphere coupling.« less

AVHRR, MODIS, and VIIRS radiometric stability and consistency in SST bands

NASA Astrophysics Data System (ADS)

Liang, XingMing; Ignatov, Alexander

2013-06-01

Monitoring of IR Clear-Sky Radiances over Oceans for SST (MICROS; www.star.nesdis.noaa.gov/sod/sst/micros) is NESDIS near-real time web-based radiance monitoring system. It analyzes Model (Community Radiative Transfer Model, CRTM) minus Observation (M-O) biases in brightness temperatures (BT) in three bands centered at 3.7 (IR37), 11 (IR11), and 12 µm (IR12), for several AVHRR (NOAA-16, -17, -18, -19, Metop-A, -B), VIIRS (Suomi National Polar Partnership, S-NPP), and MODIS (Terra, Aqua) sensors. Double-differences (DD) are employed to check BTs for radiometric stability and consistency. All sensors are stable, with the exception of two AVHRRs, onboard NOAA-16 and to a lesser extent NOAA-18, and generally consistent. VIIRS onboard S-NPP, launched in October 2011, is well in-family, especially after its calibration was fine-tuned on 7 March 2012. MODIS M-O biases were initially out-of-family by up to -0.6 K, due to incorrect CRTM transmittance coefficients. Following MICROS feedback, CRTM Team updated coefficients and brought MODIS back in-family. Terra and Aqua BTs are very consistent in IR11 and IR12 but show cross-platform bias of 0.3 K in IR37, likely attributed to MODIS characterization. Work with MODIS Characterization Support Team is underway to resolve this. Initial analyses of AVHRR onboard Metop-B launched in September 2012 suggest that its BTs are offset from Metop-A by up to ˜0.3 K. Overall, MICROS DDs are well suited to evaluate the sensors stability, but dedicated effort is needed to ensure consistent radiative transfer modeling (RTM) calculations for various sensors before DDs can be used in Global Space-based Inter-Calibration System (GSICS) quantitative applications.

Practical Application and Obstacles of AVHRR Thermal Data for Estimation of Effusion Rates at Tolbachik Volcano, Kamchatka Peninsula, Russian Federation

NASA Astrophysics Data System (ADS)

McAlpin, D. B.; Meyer, F. J.; Webley, P. W.

2017-12-01

Using thermal data from Advanced Very High Resolution Radiometer (AVHRR) sensors, we investigated algorithms to estimate the effusive volume of lava flows from the 2012-13 eruption of Tolbachik Volcano with high temporal resolution. AVHRR are polar orbiting, radiation detection instruments that provide reflectance and radiance data in six spectral bands with a ground resolution of 1.1 km². During the Tolbachik eruption of 2012-13, active AVHRR instruments were available aboard four polar orbiting platforms. Although the primary purpose of the instruments is climate and ocean studies, their multiple platforms provide global coverage at least twice daily, with data for all regions of the earth no older than six hours. This frequency makes the AVHRR instruments particularly suitable for the study of volcanic activity. While methods for deriving effusion rates from thermal observations have been previously published, a number of topics complicate their practical application. In particular, these include (1) unknown material parameters used in the estimation process; (2) relatively coarse resolution of thermal sensors; (3) optimizing a model to describe the number of thermal regimes within each pixel and (4) frequent saturation issues in thermal channels. We present ongoing investigations into effusion rate estimation from AVHRR data using the 2012-13 eruption of Tolbachik Volcano as a test event. For this eruption we studied approaches for coping with issues (1) - (4) to pave the way to a more operational implementation of published techniques. To address (1), we used Monte Carlo simulations to understand the sensitivity of effusion rate estimates to changes in material parameters. To study (2) and (3) we compared typical two-component (exposed lava on ambient background) and three-component models (exposed lava, cooled crust, ambient background) for their relative performance. To study issue (4), we compared AVHRR-derived effusion rates to reference data derived from

A CERES-like Cloud Property Climatology Using AVHRR Data

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Yost, C. R.; Trepte, Q.; Bedka, S. T.; Sun-Mack, S.; Doelling, D.

2015-12-01

Clouds affect the climate system by modulating the radiation budget and distributing precipitation. Variations in cloud patterns and properties are expected to accompany changes in climate. The NASA Clouds and the Earth's Radiant Energy System (CERES) Project developed an end-to-end analysis system to measure broadband radiances from a radiometer and retrieve cloud properties from collocated high-resolution MODerate-resolution Imaging Spectroradiometer (MODIS) data to generate a long-term climate data record of clouds and clear-sky properties and top-of-atmosphere radiation budget. The first MODIS was not launched until 2000, so the current CERES record is only 15 years long at this point. The core of the algorithms used to retrieve the cloud properties from MODIS is based on the spectral complement of the Advanced Very High Resolution Radiometer (AVHRR), which has been aboard a string of satellites since 1978. The CERES cloud algorithms were adapted for application to AVHRR data and have been used to produce an ongoing CERES-like cloud property and surface temperature product that includes an initial narrowband-based radiation budget. This presentation will summarize this new product, which covers nearly 37 years, and its comparability with cloud parameters from CERES, CALIPSO, and other satellites. Examples of some applications of this dataset are given and the potential for generating a long-term radiation budget CDR is also discussed.

Engima of a thermal anomaly - A TM/AVHRR study of the volcanic Arabian highlands

NASA Technical Reports Server (NTRS)

Blodget, H. W.; Andre, C. G.; Masuoka, P. M.

1987-01-01

Discovery of a large thermal anomaly in the western Arabian highlands on Landsat TM imagery is reported. The anomaly, 15 C warmer than surroundings, forms a 2-km-wide arc around the southern flank of Jebel Chada, a volcano active in 1256 AD. It is recorded by AVHRR imagery as well, despite the 1.1-km spatial resolution of this sensor. Air photos and geologic maps show no bedrock unit that corresponds to the anomaly. Digital techniques were applied to the TM and AVHRR data, including contrast enhancement, density slicing, principal components analysis, and construction of multiband composite images. It is concluded that the anomaly results from a thin cover of volcanic ash or cinder that is optically indistinguishable from underlying basalt, rather than from internal (volcanic or hydrologic) heat sources.

Seasonal monitoring of soil erosion at regional scale: An application of the G2 model in Crete focusing on agricultural land uses

NASA Astrophysics Data System (ADS)

Panagos, Panagos; Christos, Karydas; Cristiano, Ballabio; Ioannis, Gitas

2014-04-01

A new soil erosion model, namely G2, was applied in the island of Crete with a focus on agricultural land uses, including potential grazing lands. The G2 model was developed within the Geoland2 project as an agro-environmental service in the framework of the Global Monitoring for Environment and Security (GMES, now Copernicus) initiative. The G2 model takes advantage of the empirical background of the Universal Soil Loss Equation (USLE) and the Gavrilovic model, together with readily available time series of vegetation layers and 10-min rainfall intensity data to produce monthly time-step erosion risk maps at 300 m cell size. The innovations of the G2 model include the implementation of land-use influence parameters based on empirical data and the introduction of a corrective term in the estimation of the topographic influence factor. The mean annual erosion rate in Crete was found to be 8.123 t ha-1. The season from October to January (the rainy season in Crete) was found to be the most critical, accounting for 80% of the annual erosion in the island. Seasonal erosion figures proved to be crucial for the identification of erosion hotspots and of risky land uses. In Crete, high annual erosion figures were detected in natural grasslands and shrublands (14.023 t ha-1), mainly due to the intensification of livestock grazing during the past decades. The G2 model allows for the integrated spatio-temporal monitoring of soil erosion per land-use type based on moderate data input requirements and existing datasets.

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

Ellis, J.E.; Swift, D.M.; Hart, T.C.

Landsat multi-spectral scanner (MSS) imagery was used to develop a vegetation type-biomass map of the 84,000 Km/sup 2/ Turkana District, Kenya. NOAA satellite advanced very high resolution radiometry (AVHRR) imagery was overlaid on the MSS map to trace the seasonal and annual dynamics of vegetation communities used by Turkana pastoral nomads, 1981-1984. Four regions (sub-sectional territories) were compared with respect to peak herbaceous biomass, woody canopy cover, and seasonal fluxes in total green biomass. Results demonstrated major variations among regions and between wet and dry season ranges within regions. Pastoral land use patterns appear to minimize effects of seasonal vegetationmore » fluxes on livestock herds.« less

Identifying high production, low production and degraded rangelands in Senegal with normalized difference vegetation index data

USGS Publications Warehouse

Tappan, G. Gray; Wood, Lynette; Moore, Donald G.

1993-01-01

Seasonal herbaceous vegetation production on Senegal's native rangelands exhibits high spatial and temporal variability. This variability can be monitored using normalized difference vegetation index (NDVI) data computed from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) image data. Although annual fluctuations in rainfall account for some of the variability, numerous long-term production patterns are evident in the AVHRR time-series data. Different n productivity reflect variations in the region's climate, topography, soils, and land use. Areas of overgrazing and intensive cultivation have caused long-term soil and vegetation degradation. Rangelands of high and low productivity, and degraded rangelands were identified using NDVI. Time-series image data from 1987 though 1992 were used to map relative rangeland productivity. The results were compared to detailed resource maps on soils, vegetation and land use. Much of the variation in rangeland productivity correlated well to the known distribution of resources. The study developed an approach that identified a number of areas of degraded soils and low vegetation production.

User's guide to image processing applications of the NOAA satellite HRPT/AVHRR data. Part 1: Introduction to the satellite system and its applications. Part 2: Processing and analysis of AVHRR imagery

NASA Technical Reports Server (NTRS)

Huh, Oscar Karl; Leibowitz, Scott G.; Dirosa, Donald; Hill, John M.

1986-01-01

The use of NOAA Advanced Very High Resolution Radar/High Resolution Picture Transmission (AVHRR/HRPT) imagery for earth resource applications is provided for the applications scientist for use within the various Earth science, resource, and agricultural disciplines. A guide to processing NOAA AVHRR data using the hardware and software systems integrated for this NASA project is provided. The processing steps from raw data on computer compatible tapes (1B data format) through usable qualitative and quantitative products for applications are given. The manual is divided into two parts. The first section describes the NOAA satellite system, its sensors, and the theoretical basis for using these data for environmental applications. Part 2 is a hands-on description of how to use a specific image processing system, the International Imaging Systems, Inc. (I2S) Model 75 Array Processor and S575 software, to process these data.

Linking Landsat observations with MODIS derived Land Surface Phenology data to map agricultural expansion and contraction in Russia

NASA Astrophysics Data System (ADS)

Caliskan, S.; de Beurs, K.

2010-12-01

Direct human impacts on the land surface are especially pronounced in agricultural regions that cover a substantial portion of the global land surface: 12% of the terrestrial surface is under active agricultural management. Crops display phenologies distinct from natural vegetation; the growing seasons are often shifted in time, crop establishment is generally fast and the vegetation is rapidly removed at harvest. Previously we have demonstrated that agricultural land abandonment alters land surface phenology sufficiently to be detectable from a time series of coarse resolution imagery. With land surface phenology models based on accumulated growing degree-days (AGDD) and AVHRR NDVI, we demonstrated that abandoned croplands covered with native grasses and weeds typically greened-up and peaked sooner than active croplands. Here we present an expansion of these analyses for the MODIS time period with the ultimate goal to map agricultural abandonment and expansion in European Russia from 2000 to 2010. We used the 8-day, 1km L3 Land Surface Temperature data (MOD11A2) to generate the accumulated growing degree days and the 16-day L3 Nadir BRDF-Adjusted reflectance data at 500m resolution (MCD43A4) to calculate NDVI. We calculated phenological metrics based on three methods: 1) Double-logistic models such as those applied to produce the standard MODIS phenology product (MOD12Q2); 2) A combination of NDII and NDVI; this method has been shown to provide start/end of season measurement closest to field observations in snowy areas; and 3) A quadratic model linking accumulated growing degree days and vegetation indices which we successfully applied in agricultural areas of Kazakhstan and semi-arid Africa. We selected Landsat imagery for two vastly different regions in Russia and present a Landsat-guided probabilistic detection of abandoned and active croplands for all available years of the MODIS image time series (2000-2010). For each region, we selected at least two images

What drives the seasonal pattern of δ13C in the net land-atmosphere CO2 exchange across the United States?

NASA Astrophysics Data System (ADS)

Raczka, B. M.; Dlugokencky, E. J.; Ehleringer, J. R.; Lai, C. T.; Pataki, D. E.; Saleska, S. R.; Torn, M. S.; Vaughn, B. H.; Wehr, R. A.; Bowling, D. R.

2016-12-01

The seasonal pattern of δ13C of atmospheric CO2 depends upon both local and non-local land-atmosphere exchange and atmospheric transport. It has been suggested that the seasonal pattern is driven primarily from local variation in the δ13C of the net CO2 flux (exchange between vegetation and the atmosphere) as a result of variation of stomatal conductance of the vegetation. Here we study local variation of δ13C of the land-atmosphere exchange at 7 sites across the United States representing forests (Harvard, Howland, Niwot Ridge, Wind River), grasslands (Southern Great Plains, Rannell Prairie) and an urban center (Salt Lake City). Using a simple 2-part mixing model with background corrections we find that the δ13C of the net exchange of CO2 was most enriched at the grassland sites (-18.9 o/oo), and most depleted at the urban site (-29.6 o/oo) due to the contribution of C4 photosynthesis and fossil fuel emissions, respectively. The amplitude of the seasonal cycle was most pronounced at the C3/C4 grassland and the urban sites. In contrast, the forested sites have a reduced seasonal cycle, and remain almost constant during the growing season (0.49 o/oo change). Furthermore, by accounting for relatively fast δ13C variations in non-local sources at Niwot Ridge we find that the seasonal pattern in δ13C of net exchange is eliminated altogether. These results support the idea that a coherent, global seasonal pattern in δ13C of net exchange is influenced by seasonal transitions in C3/C4 grass, and the intensity and seasonal timing of fossil fuel emissions. This will have important implications for studies that use δ13C to constrain large-scale carbon fluxes.

Long-term vegetation activity trends in the Iberian Peninsula and The Balearic Islands using high spatial resolution NOAA-AVHRR data (1981 - 2015).

NASA Astrophysics Data System (ADS)

Martin-Hernandez, Natalia; Vicente-Serrano, Sergio; Azorin-Molina, Cesar; Begueria-Portugues, Santiago; Reig-Gracia, Fergus; Zabalza-Martínez, Javier

2017-04-01

We have analysed trends in the Normalized Difference Vegetation Index (NDVI) in the Iberian Peninsula and The Balearic Islands over the period 1981 - 2015 using a new high resolution data set from the entire available NOAA - AVHRR images (IBERIAN NDVI dataset). After a complete processing including geocoding, calibration, cloud removal, topographic correction and temporal filtering, we obtained bi-weekly time series. To assess the accuracy of the new IBERIAN NDVI time-series, we have compared temporal variability and trends of NDVI series with those results reported by GIMMS 3g and MODIS (MOD13A3) NDVI datasets. In general, the IBERIAN NDVI showed high reliability with these two products but showing higher spatial resolution than the GIMMS dataset and covering two more decades than the MODIS dataset. Using the IBERIAN NDVI dataset, we analysed NDVI trends by means of the non-parametric Mann-Kendall test and Theil-Sen slope estimator. In average, vegetation trends in the study area show an increase over the last decades. However, there are local spatial differences: the main increase has been recorded in humid regions of the north of the Iberian Peninsula. The statistical techniques allow finding abrupt and gradual changes in different land cover types during the analysed period. These changes are related with human activity due to land transformations (from dry to irrigated land), land abandonment and forest recovery.

Calibration of the AVHRR visible and near IR channels using radiances measured over remote ocean areas

NASA Technical Reports Server (NTRS)

Vermote, Eric F.; Vassiliou, George D.; Kaufman, Yoram J.; Holben, Brent N.

1992-01-01

An inflight absolute calibration method has been adapted and applied to channel 1 of the AVHRR. The approach is based on AVHRR observations in channels 1, 2 and 4. A rigorous cloud screening is performed, based on the homogeneity of the data in channel 1 and 2 and on the temperature in channel 4. In a combined approach, the off-nadir view satellite count in channel 2 is used to detect the aerosol optical thickness and loading and the count of channel 1 is used to calibrate this channel, based on the predictable Rayleigh scattering component. Water vapor data are used, and the channels are intercalibrated using the ratio between channels 1 and 2 over the glint region.

Comparison of TOMS and AVHRR volcanic ash retrievals from the August 1992 eruption of Mt. Spurr

USGS Publications Warehouse

Krotkov, N.A.; Torres, O.; Seftor, C.; Krueger, A.J.; Kostinski, A.; Rose, William I.; Bluth, G.J.S.; Schneider, D.; Schaefer, S.J.

1999-01-01

On August 19, 1992, the Advanced Very High Resolution Radiometer (AVHRR) onboard NOAA-12 and NASA's Total Ozone Mapping Spectrometer (TOMS) onboard the Nimbus-7 satellite simultaneously detected and mapped the ash cloud from the eruption of Mt. Spurr, Alaska. The spatial extent and geometry of the cloud derived from the two datasets are in good agreement and both AVHRR split window IR (11-12??m brightness temperature difference) and the TOMS UV Aerosol Index (0.34-0.38??m ultraviolet backscattering and absorption) methods give the same range of total cloud ash mass. Redundant methods for determination of ash masses in drifting volcanic clouds offer many advantages for potential application to the mitigation of aircraft hazards.

A Real-Time MODIS Vegetation Composite for Land Surface Models and Short-Term Forecasting

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Kumar, Sujay V.; Jedlovec, Gary J.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center is producing real-time, 1- km resolution Normalized Difference Vegetation Index (NDVI) gridded composites over a Continental U.S. domain. These composites are updated daily based on swath data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the polar orbiting NASA Aqua and Terra satellites, with a product time lag of about one day. A simple time-weighting algorithm is applied to the NDVI swath data that queries the previous 20 days of data to ensure a continuous grid of data populated at all pixels. The daily composites exhibited good continuity both spatially and temporally during June and July 2010. The composites also nicely depicted high greenness anomalies that resulted from significant rainfall over southwestern Texas, Mexico, and New Mexico during July due to early-season tropical cyclone activity. The SPoRT Center is in the process of computing greenness vegetation fraction (GVF) composites from the MODIS NDVI data at the same spatial and temporal resolution for use in the NASA Land Information System (LIS). The new daily GVF dataset would replace the monthly climatological GVF database (based on Advanced Very High Resolution Radiometer [AVHRR] observations from 1992-93) currently available to the Noah land surface model (LSM) in both LIS and the public version of the Weather Research and Forecasting (WRF) model. The much higher spatial resolution (1 km versus 0.15 degree) and daily updates based on real-time satellite observations have the capability to greatly improve the simulation of the surface energy budget in the Noah LSM within LIS and WRF. Once code is developed in LIS to incorporate the daily updated GVFs, the SPoRT Center will conduct simulation sensitivity experiments to quantify the impacts and improvements realized by the MODIS real-time GVF data. This presentation will describe the methodology used to develop the 1-km MODIS NDVI composites and

Spatial and Temporal Variation of PATMOS-x AVHRR Lake Surface Temperatures in the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

White, C.; Heidinger, A. K.; Ackerman, S. A.; McIntyre, P. B.

2017-12-01

A thirty-four year lake surface water temperature (LSWT) time series over the North American Great Lakes was extracted from NOAA's Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC). The time series was cloud-cleared using the NOAA Pathfinder Atmospheres Extended (PATMOS-x) climate dataset and the Clouds from AVHRR Extended System (CLAVR-x) processing system, and was subsampled to a regular 0.05° grid. LSWT coefficients for each AVHRR platform were fit to NOAA National Data Buoy Center buoys with historical records spanning 1982 to 2016. Satellite to buoy matchups indicate an RMSE of 0.72 K for the entire time series across all five lakes. An empirically fit diurnal correction was applied to correct for orbital drift and varying observation times of NOAA-7,9,11,12,14-19, Metop-1 and Metop-2. Ordinary linear regression slopes on monthly mean LSWT show strong spatial heterogeneity in the long-term LSWT trends both within each lake and between lakes. Differences in long-term trends using nighttime only, daytime only, and both day and night are examined. Additionally, a coastal upwelling signal can be identified from the time series along with the indication of an earlier onset of spring stratification.

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

NASA Astrophysics Data System (ADS)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

Historic AVHRR Processing in the Eumetsat Climate Monitoring Satellite Application Facility (cmsaf) (Invited)

NASA Astrophysics Data System (ADS)

Karlsson, K.

2010-12-01

The EUMETSAT CMSAF project (www.cmsaf.eu) compiles climatological datasets from various satellite sources with emphasis on the use of EUMETSAT-operated satellites. However, since climate monitoring primarily has a global scope, also datasets merging data from various satellites and satellite operators are prepared. One such dataset is the CMSAF historic GAC (Global Area Coverage) dataset which is based on AVHRR data from the full historic series of NOAA-satellites and the European METOP satellite in mid-morning orbit launched in October 2006. The CMSAF GAC dataset consists of three groups of products: Macroscopical cloud products (cloud amount, cloud type and cloud top), cloud physical products (cloud phase, cloud optical thickness and cloud liquid water path) and surface radiation products (including surface albedo). Results will be presented and discussed for all product groups, including some preliminary inter-comparisons with other datasets (e.g., PATMOS-X, MODIS and CloudSat/CALIPSO datasets). A background will also be given describing the basic methodology behind the derivation of all products. This will include a short historical review of AVHRR cloud processing and resulting AVHRR applications at SMHI. Historic GAC processing is one of five pilot projects selected by the SCOPE-CM (Sustained Co-Ordinated Processing of Environmental Satellite data for Climate Monitoring) project organised by the WMO Space programme. The pilot project is carried out jointly between CMSAF and NOAA with the purpose of finding an optimal GAC processing approach. The initial activity is to inter-compare results of the CMSAF GAC dataset and the NOAA PATMOS-X dataset for the case when both datasets have been derived using the same inter-calibrated AVHRR radiance dataset. The aim is to get further knowledge of e.g. most useful multispectral methods and the impact of ancillary datasets (for example from meteorological reanalysis datasets from NCEP and ECMWF). The CMSAF project is

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.

1999-01-01

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 1 2013-04-01 2013-04-01 false Can the number of animals and/or season of use be... AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or... an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified on...

25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false Can the number of animals and/or season of use be... AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or... an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified on...

25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Can the number of animals and/or season of use be... AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or... an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified on...

25 CFR 166.308 - Can the number of animals and/or season of use be modified on the permitted land if I graze...

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false Can the number of animals and/or season of use be... AND WATER GRAZING PERMITS Land and Operations Management § 166.308 Can the number of animals and/or... an on-and-off grazing permit? Yes. The number of animals and/or season of use may be modified on...

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan;

Role of CO2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: a multimodel analysis

NASA Astrophysics Data System (ADS)

Zhao, Fang; Zeng, Ning; Asrar, Ghassem; Friedlingstein, Pierre; Ito, Akihiko; Jain, Atul; Kalnay, Eugenia; Kato, Etsushi; Koven, Charles D.; Poulter, Ben; Rafique, Rashid; Sitch, Stephen; Shu, Shijie; Stocker, Beni; Viovy, Nicolas; Wiltshire, Andy; Zaehle, Sonke

2016-09-01

We examined the net terrestrial carbon flux to the atmosphere (FTA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40 % compared to atmospheric inversions. Global FTA amplitude increase (19 ± 8 %) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56 %, -3 ± 74 and 20 ± 30 % to rising CO2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO2 fertilization is the strongest control - with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global FTA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between FTA amplitude increase and increase in land carbon sink (R2 = 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in

Role of CO 2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

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

Zhao, Fang; Zeng, Ning; Asrar, Ghassem

We examined the net terrestrial carbon flux to the atmosphere (F TA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations.more » However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use

Role of CO 2, climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

DOE PAGES

Zhao, Fang; Zeng, Ning; Asrar, Ghassem; ...

2016-09-14

We examined the net terrestrial carbon flux to the atmosphere (F TA) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations.more » However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2, climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA: some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use

Results of calibrations of the NOAA-11 AVHRR made by reference to calibrated SPOT imagery at White Sands, N.M

NASA Technical Reports Server (NTRS)

Nianzeng, Che; Grant, Barbara G.; Flittner, David E.; Slater, Philip N.; Biggar, Stuart F.; Jackson, Ray D.; Moran, M. S.

1991-01-01

The calibration method reported here makes use of the reflectances of several large, uniform areas determined from calibrated and atmospherically corrected SPOT Haute Resolution Visible (HRV) scenes of White Sands, New Mexico. These reflectances were used to predict the radiances in the first two channels of the NOAA-11 Advanced Very High Resolution Radiometer (AVHRR). The digital counts in the AVHRR image corresponding to these known reflectance areas were determined by the use of two image registration techniques. The plots of digital counts versus pixel radiance provided the calibration gains and offsets for the AVHRR. A reduction in the gains of 4 and 13 percent in channels 1 and 2 respectively was found during the period 1988-11-19 to 1990-6-21. An error budget is presented for the method and is extended to the case of cross-calibrating sensors on the same orbital platform in the Earth Observing System (EOS) era.

Comparison of Ant Community Diversity and Functional Group Composition Associated to Land Use Change in a Seasonally Dry Oak Forest.

PubMed

Cuautle, M; Vergara, C H; Badano, E I

2016-04-01

Ants have been used to assess land use conversion, because they reflect environmental change, and their response to these changes have been useful in the identification of bioindicators. We evaluated ant diversity and composition associated to different land use change in a temperate forest (above 2000 m asl) in Mexico. The study was carried out in "Flor del Bosque" Park a vegetation mosaic of native Oak Forests and introduced Eucalyptus and grasslands. Species richness, dominance and diversity rarefaction curves, based on ant morphospecies and functional groups, were constructed and compared among the three vegetation types, for the rainy and the dry seasons of 2008-2009. Jaccard and Sorensen incidence-based indices were calculated to obtain similarity values among all the habitats. The Oak Forest was a rich dominant community, both in species and functional groups; the Eucalyptus plantation was diverse with low dominance. The most seasonality habitat was the grassland, with low species and high functional group diversity during the dry seasons, but the reverse pattern during the wet season. The Oak Forest was more similar to the Eucalyptus plantation than to the grassland, particularly during the dry season. Oak Forests are dominated by Cold Climate Specialists, specifically Prenolepis imparis (Say). The Eucalyptus and the grassland are characterized by generalized Myrmicinae, as Pheidole spp. and Monomorium ebenium (Forel). The conservation of the native Oak Forest is primordial for the maintenance of Cold Climate Specialist ant communities. The microclimatic conditions in this forest, probably, prevented the invasion by opportunistic species.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Surface temperature statistics over Los Angeles - The influence of land use

NASA Technical Reports Server (NTRS)

Dousset, Benedicte

1991-01-01

Surface temperature statistics from 84 NOAA AVHRR (Advanced Very High Resolution Radiometer) satellite images of the Los Angeles basin are interpreted as functions of the corresponding urban land-cover classified from a multispectral SPOT image. Urban heat islands observed in the temperature statistics correlate well with the distribution of industrial and fully built areas. Small cool islands coincide with highly watered parks and golf courses. There is a significant negative correlation between the afternoon surface temperature and a vegetation index computed from the SPOT image.

Multi-frequency SAR, SSM/I and AVHRR derived geophysical information of the marginal ice zone

NASA Technical Reports Server (NTRS)

Shuchman, R. A.; Onstott, R. G.; Wackerman, C. C.; Russel, C. A.; Sutherland, L. L.; Johannessen, O. M.; Johannessen, J. A.; Sandven, S.; Gloerson, P.

1991-01-01

A description is given of the fusion of synthetic aperture radar (SAR), special sensor microwave imager (SSM/I), and NOAA Advanced Very High Resolution Radiometer (AVHRR) data to study arctic processes. These data were collected during the SIZEX/CEAREX experiments that occurred in the Greenland Sea in March of 1989. Detailed comparisons between the SAR, AVHRR, and SSM/I indicated: (1) The ice edge position was in agreement to within 25 km, (2) The SSM/I SAR total ice concentration compared favorably, however, the SSM/I significantly underpredicted the multiyear fraction, (3) Combining high resolution SAR with SSM/I can potentially map open water and new ice features in the marginal ice zone (MIZ) which cannot be mapped by the single sensors, and (4) The combination of all three sensors provides accurate ice information as well as sea surface temperature and wind speeds.

Surface radiant flux densities inferred from LAC and GAC AVHRR data

NASA Astrophysics Data System (ADS)

Berger, F.; Klaes, D.

To infer surface radiant flux densities from current (NOAA-AVHRR, ERS-1/2 ATSR) and future meteorological (Envisat AATSR, MSG, METOP) satellite data, the complex, modular analysis scheme SESAT (Strahlungs- und Energieflüsse aus Satellitendaten) could be developed (Berger, 2001). This scheme allows the determination of cloud types, optical and microphysical cloud properties as well as surface and TOA radiant flux densities. After testing of SESAT in Central Europe and the Baltic Sea catchment (more than 400scenes U including a detailed validation with various surface measurements) it could be applied to a large number of NOAA-16 AVHRR overpasses covering the globe.For the analysis, two different spatial resolutions U local area coverage (LAC) andwere considered. Therefore, all inferred results, like global area coverage (GAC) U cloud cover, cloud properties and radiant properties, could be intercompared. Specific emphasis could be made to the surface radiant flux densities (all radiative balance compoments), where results for different regions, like Southern America, Southern Africa, Northern America, Europe, and Indonesia, will be presented. Applying SESAT, energy flux densities, like latent and sensible heat flux densities could also be determined additionally. A statistical analysis of all results including a detailed discussion for the two spatial resolutions will close this study.

Hydrologic models for land-atmosphere retrospective studies of the use of LANDSAT and AVHRR data

NASA Technical Reports Server (NTRS)

Duchon, Claude E.; Williams, T. H. Lee; Nicks, Arlin D.

1988-01-01

The use of a Geographic Information System (GIS) and LANDSAT analysis in conjunction with the Simulator for Water Resources on a Rural Basin (SWRRB) hydrologic model to examine the water balance on the Little Washita River basin is discussed. LANDSAT analysis was used to divide the basin into eight non-contiguous land covers or subareas: rangeland, grazed range, winter wheat, alfalfa/pasture, bare soil, water, woodland, and impervious land (roads, quarry). The use of a geographic information system allowed for the calculation of SWRRB model parameters in each subarea. Four data sets were constructed in order to compare SWRRB estimates of hydrologic processes using two methods of maximum LAI and two methods of watershed subdivision. Maximum LAI was determined from a continental scale map, which provided a value of 4.5 for the entire basin, and from its association with the type of land-cover (eight values). The two methods of watershed subdivision were determined according to drainage subbasin (four) and the eight land-covers. These data sets were used with the SWRRB model to obtain daily hydrologic estimates for 1985. The results of the one year analysis lead to the conclusion that the greater homogeneity of a land-cover subdivision provides better water yield estimates than those based on a drainage properties subdivision.

Does vapor pressure deficit drive the seasonality of δ 13 C of the net land-atmosphere CO 2 exchange across the United States?: The Influence of VPD on δ 13 C of NEE

DOE PAGES

Raczka, B.; Biraud, S. C.; Ehleringer, J. R.; ...

2017-08-10

The seasonal pattern of the carbon isotope content (δ 13C) of atmospheric CO 2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO 2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δ source at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ 13C variation of nonlocalmore » sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δ source at the forest sites (0.5‰variation). We did not find a consistent seasonal relationship between VPD and δ source across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δ source (5‰) dominated by seasonal transitions in C 3/C 4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ 13C of land-atmosphere CO 2 exchange (δ source) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C 3/C 4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate

Does vapor pressure deficit drive the seasonality of δ 13 C of the net land-atmosphere CO 2 exchange across the United States?: The Influence of VPD on δ 13 C of NEE

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

Raczka, B.; Biraud, S. C.; Ehleringer, J. R.

The seasonal pattern of the carbon isotope content (δ 13C) of atmospheric CO 2 depends on local and nonlocal land-atmosphere exchange and atmospheric transport. Previous studies suggested that the δ13C of the net land-atmosphere CO 2 flux (δsource) varies seasonally as stomatal conductance of plants responds to vapor pressure deficit of air (VPD). We studied the variation of δ source at seven sites across the United States representing forests, grasslands, and an urban center. Using a two-part mixing model, we calculated the seasonal δsource for each site after removing background influence and, when possible, removing δ 13C variation of nonlocalmore » sources. Compared to previous analyses, we found a reduced seasonal (March–September) variation in δ source at the forest sites (0.5‰variation). We did not find a consistent seasonal relationship between VPD and δ source across forest (or other) sites, providing evidence that stomatal response to VPD was not the cause of the global, coherent seasonal pattern in δsource. In contrast to the forest sites, grassland and urban sites had a larger seasonal variation in δ source (5‰) dominated by seasonal transitions in C 3/C 4 grass productivity and in fossil fuel emissions, respectively. Our findings were sensitive to the location used to account for atmospheric background variation within the mixing model method that determined δsource. Special consideration should be given to background location depending on whether the intent is to understand site level dynamics or regional scale impacts of land-atmosphere exchange. The seasonal amplitude in δ 13C of land-atmosphere CO 2 exchange (δ source) varied across land cover types and was not driven by seasonal changes in vapor pressure deficit. The largest seasonal amplitudes of δsource were at grassland and urban sites, driven by changes in C 3/C 4 grass productivity and fossil fuel emissions, respectively. Mixing model approaches may incorrectly calculate

Revisiting AVHRR Tropospheric Aerosol Trends Using Principal Component Analysis

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

The advanced very high resolution radiometer (AVHRR) satellite instruments provide a nearly 25 year continuous record of global aerosol properties over the ocean. It offers valuable insights into the long-term change in global aerosol loading. However, the AVHRR data record is heavily influenced by two volcanic eruptions, El Chichon on March 1982 and Mount Pinatubo on June 1991. The gradual decay of volcanic aerosols may last years after the eruption, which potentially masks the estimation of aerosol trends in the lower troposphere, especially those of anthropogenic origin. In this study, we show that a principal component analysis approach effectively captures the bulk of the spatial and temporal variability of volcanic aerosols into a single mode. The spatial pattern and time series of this mode provide a good match to the global distribution and decay of volcanic aerosols. We further reconstruct the data set by removing the volcanic aerosol component and reestimate the global and regional aerosol trends. Globally, the reconstructed data set reveals an increase of aerosol optical depth from 1985 to 1990 and decreasing trend from 1994 to 2006. Regionally, in the 1980s, positive trends are observed over the North Atlantic and North Arabian Sea, while negative tendencies are present off the West African coast and North Pacific. During the 1994 to 2006 period, the Gulf of Mexico, North Atlantic close to Europe, and North Africa exhibit negative trends, while the coastal regions of East and South Asia, the Sahel region, and South America show positive trends.

Characteristics of vegetation phenology over the Alaskan landscape using AVHRR time-series data

USGS Publications Warehouse

Markon, Carl J.; Fleming, Michael D.; Binnian, Emily F.

1995-01-01

Advanced Very High Resolution Radiometer (AVHRR) satellite data were acquired and composited into twice-a-month periods from 1 May 1991 to 15 October 1991 in order to map vegetation characteristics of the Alaskan landscape. Unique spatial and temporal qualities of the AVHRR data provide information that leads to a better understanding of regional biophysical characteristics of vegetation communities and patterns. These data provided synoptic views of the landscape and depicted phenological diversity, temporal vegetation phenology (green-up, peak of green, and senescence), photosynthetic activity, and regional landscape patterns. Products generated from the data included a phenological class map, phenological composite maps (onset, peak, and duration), and photosynthetic activity maps (mean and maximum greenness). The time-series data provide opportunities to study phenological processes at small landscape scales over time periods of weeks, months, and years. Regional patterns identified on some of the maps are unique to specific areas; others correspond to biophysical or ecoregional boundaries. The data provide new insights to landscape processes, ecology, and landscape physiognomy that allow scientists to look at landscapes in ways that were previously difficult to achieve.

Downscaling of Seasonal Landsat-8 and MODIS Land Surface Temperature (LST) in Kolkata, India

NASA Astrophysics Data System (ADS)

Garg, R. D.; Guha, S.; Mondal, A.; Lakshmi, V.; Kundu, S.

2017-12-01

The quality of life of urban people is affected by urban heat environment. The urban heat studies can be carried out using remotely sensed thermal infrared imagery for retrieving Land Surface Temperature (LST). Currently, high spatial resolution (<200 m) thermal images are limited and their temporal resolution is low (e.g., 17 days of Landsat-8). Coarse spatial resolution (1000 m) and high temporal resolution (daily) thermal images of MODIS (Moderate Resolution Imaging Spectroradiometer) are frequently available. The present study is to downscale spatially coarser resolution of the thermal image to fine resolution thermal image using regression based downscaling technique. This method is based on the relationship between (LST) and vegetation indices (e.g., Normalized Difference Vegetation Index or NDVI) over a heterogeneous landscape. The Kolkata metropolitan city, which experiences a tropical wet-and-dry type of climate has been selected for the study. This study applied different seasonal open source satellite images viz., Landsat-8 and Terra MODIS. The Landsat-8 images are aggregated at 960 m resolution and downscaled into 480, 240 120 and 60 m. Optical and thermal resolution of Landsat-8 and MODIS are 30 m and 60 m; 250 m and 1000 m respectively. The homogeneous land cover areas have shown better accuracy than heterogeneous land cover areas. The downscaling method plays a crucial role while the spatial resolution of thermal band renders it unable for advanced study. Key words: Land Surface Temperature (LST), Downscale, MODIS, Landsat, Kolkata

Seasonal variation of nitrogen-concentration in the surface water and its relationship with land use in a catchment of northern China.

PubMed

Chen, Li-ding; Peng, Hong-jia; Fu, Bo-Jie; Qiu, Jun; Zhang, Shu-rong

2005-01-01

Surface waters can be contaminated by human activities in two ways: (1) by point sources, such as sewage treatment discharge and storm-water runoff; and (2) by non-point sources, such as runoff from urban and agricultural areas. With point-source pollution effectively controlled, non-point source pollution has become the most important environmental concern in the world. The formation of non-point source pollution is related to both the sources such as soil nutrient, the amount of fertilizer and pesticide applied, the amount of refuse, and the spatial complex combination of land uses within a heterogeneous landscape. Land-use change, dominated by human activities, has a significant impact on water resources and quality. In this study, fifteen surface water monitoring points in the Yuqiao Reservoir Basin, Zunhua, Hebei Province, northern China, were chosen to study the seasonal variation of nitrogen concentration in the surface water. Water samples were collected in low-flow period (June), high-flow period (July) and mean-flow period (October) from 1999 to 2000. The results indicated that the seasonal variation of nitrogen concentration in the surface water among the fifteen monitoring points in the rainfall-rich year is more complex than that in the rainfall-deficit year. It was found that the land use, the characteristics of the surface river system, rainfall, and human activities play an important role in the seasonal variation of N-concentration in surface water.

[Community structure and seasonal change of soil micro-arthropodes in the Lower Reaches of Liaohe River Plain under different land utilization].

PubMed

Ke, Xin; Liang, Wenju; Yu, Wantai; Xie, Rongdong; Weng, Chaolian; Yang, Yiming; Yin, Wenying

2004-04-01

The data on the soil micro-arthropodes under four land utilization types (fallow, forest, upland field and paddy) in the Lower Reaches of Liaohe River Plain were collected in a period from October 2000 to October 2001. Using the community parameters of population density, group richness, diversity index and evenness, the community structure and its seasonal changes were described. There were 12 groups of soil micro-arthropodes in this region, and of the groups, Collembola and Acarina were dominant, and Diptera, Coleoptera and Hymenoptera were often seen in fallow, forest and upland field, while Collembola, Acarina and Diptera were dominant in paddy. Both land utilization and seasonal change influenced the population density, group richness and diversity index of soil micro-arthropodes. The vertical distribution in both density and group number of arthropods in soil was in the order of surface > middle > bottom.

Seasonal albedo of an urban/rural landscape from satellite observations

NASA Technical Reports Server (NTRS)

Brest, Christopher L.

1987-01-01

Using data from 27 calibrated Landsat observations of the Hartford, Connecticut area, the spatial distribution and seasonal variation of surface reflectance and albedo were examined. Mean values of visible reflectance, near-IR reflectance, and albedo are presented (for both snow-free and snow-cover observations) according to 14 land use/land cover categories. A diversity of albedo values was found to exist in this type of environment, associated with land cover. Many land-cover categories display a seasonal dependence, with intracategory seasonal differences being of comparable magnitude to intercategory differences. Key factors in determining albedo (and its seasonal dynamics) are the presence or absence of vegetation and the canopy structure. Snow-cover/snow-free differences range from a few percent (for urban land covers) to over 40 percent (for low-canopy vegetation).

On the seasonal phytoplankton concentration and sea surface temperature cycles of the Gulf of Mexico as determined by satellites

NASA Technical Reports Server (NTRS)

Mueller-Karger, Frank E.; Walsh, John J.; Meyers, Mark B.; Evans, Robert H.

1991-01-01

Multiyear series of coastal zone color scanner (CZCS) and AVHRR observations are presently used to derive monthly climatologies of near-surface phytoplankton pigment concentration and SST for the Gulf of Mexico; these, in combination with 1946-1987 SST data and NOAA hydrographic profile data covering 1914-1985, show that the most important single factor controlling seasonal cycle surface-pigment concentration is the depth of the mixed layer. The CZCS images indicate that seasonal variation seaward of the continental shelf is synchronous throughout the Gulf. The combination of ocean color and IR images allows year-round observation of surface circulation spatial structure in the Gulf, as well as of the dispersal pattern of the Mississippi River's plume.

Seasonal Response of Overland Flow and Sediment Loading to Climate and Land Use Land Cover Change in the Apalachicola River, Florida

NASA Astrophysics Data System (ADS)

Hovenga, P. A.; Wang, D.; Medeiros, S. C.; Hagen, S. C.

2015-12-01

Located in Florida's panhandle, the Apalachicola River is the southernmost reach of the Apalachicola-Chattahoochee-Flint (ACF) River basin. Streamflow and sediment drains to Apalachicola Bay within the Northern Gulf of Mexico, resulting in a direct influence on the ecology of the region, in particular seagrass and oyster production. This study examines the seasonal response of overland flow and sediment loading in the Apalachicola River under projected climate change scenarios and land use land cover (LULC) change. A hydrologic model using the Soil Water Assessment Tool (SWAT) was developed for the Apalachicola region to simulate daily discharge and sediment load under present (circa 2000) and future conditions (circa 2100) to understand how parameters respond over a seasonal time frame to changes in climate only, LULC only, and coupled climate / LULC. These physically-based models incorporate digital elevation model (DEM), LULC, soil maps, climate data, and management controls. Long Ashton Research Station-Weather Generator (LARS-WG) was used to create stochastic temperature and precipitation inputs from four Global Climate Models (GCM), each under Intergovernmental Panel on Climate Change (IPCC) carbon emission scenarios for A1B, A2, and B1. These scenarios represent potential future emissions resulting from a range driving forces, e.g. social, economic, environmental, and technologic. Projected 2100 LULC data provided by the United States Geological Survey (USGS) EROS Center was incorporated for each corresponding IPCC scenario. Results from this study can be used to further understand climate and LULC implications to the Apalachicola Bay and surrounding region as well as similar fluvial estuaries while providing tools to better guide management and mitigation practices.

Assessing satellite-derived start-of-season measures in the conterminous USA

USGS Publications Warehouse

Schwartz, Mark D.; Reed, Bradley C.; White, Michael A.

2002-01-01

National Oceanic and Atmospheric Administration (NOAA)-series satellites, carrying advanced very high-resolution radiometer (AVHRR) sensors, have allowed moderate resolution (1 km) measurements of the normalized difference vegetation index (NDVI) to be collected from the Earth's land surfaces for over 20 years. Across the conterminous USA, a readily accessible and decade-long data set is now available to study many aspects of vegetation activity in this region. One feature, the onset of deciduous plant growth at the start of the spring season (SOS) is of special interest, as it appears to be crucial for accurate computation of several important biospheric processes, and a sensitive measure of the impacts of global change. In this study, satellite-derived SOS dates produced by the delayed moving average (DMA) and seasonal midpoint NDVI (SMN) methods, and modelled surface phenology (spring indices, SI) were compared at widespread deciduous forest and mixed woodland sites during 1990–93 and 1995–99, and these three measures were also matched to native species bud-break data collected at the Harvard Forest (Massachusetts) over the same time period. The results show that both SOS methods are doing a modestly accurate job of tracking the general pattern of surface phenology, but highlight the temporal limitations of biweekly satellite data. Specifically, at deciduous forest sites: (1) SMN SOS dates are close in time to SI first bloom dates (average bias of +0.74 days), whereas DMA SOS dates are considerably earlier (average bias of −41.24 days) and also systematically earlier in late spring than in early spring; (2) SMN SOS tracks overall yearly trends in deciduous forests somewhat better than DMA SOS, but with larger average error (MAEs 8.64 days and 7.37 days respectively); and (3) error in both SOS techniques varies considerably by year. Copyright © 2002 Royal Meteorological Society.

Watershed Land Use and Seasonal Variation Constrain the ...

EPA Pesticide Factsheets

While watershed and local scale controls on stream metabolism have been independently investigated, little is known about how controls exerted at these different scales interact to determine stream metabolic rates, or how these interactions vary across seasons. To address this knowledge gap, we measured ecosystem metabolism in four urban and four reference streams in northern Kentucky, USA, with paired closed and open riparian canopies, during each of the four seasons of the year. Gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) were all best predicted by models with season as a main effect, but interactions between season, canopy and watershed varied for each response. Urban streams exhibited higher GPP during most seasons, likely due to elevated nutrient loads. Open canopy reaches in both urban and forested streams supported higher rates of GPP than the closed canopy reaches during the summer and fall when the overhead vegetation shaded the closed reaches. Surprisingly, the effect of canopy cover on GPP was similar among urban and forested streams. The combination of watershed and local-scale controls resulted in urban streams that alternated between net heterotrophy (NEP 0) between seasons with and without dense canopy cover. This finding has management relevance because net production can lead to accumulation of algal biomass and associated issues like dissolved oxygen sags at night. Our study reinforces

Does Mexican Land Management Influence US Southwest Rainfall? Effects of Vegetation Seasonality and Land Use Change on Atmospheric Moisture Transport in the North American Monsoon

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Vivoni, E. R.

2013-12-01

Southern Arizona and New Mexico receive 30-50% of their annual rainfall in the summer, as part of the North American Monsoon (NAM). Modeling studies suggest that 15-25% of this rainfall first falls on Mexican land, is transpired by vegetation, and subsequently is transported northward across the border to the US. The main source regions in Mexico lie in the subtropical scrub and tropical deciduous forests in the foothills of the Sierra Madre Occidental, in the states of Sinaloa and Sonora. A key characteristic of these natural ecosystems is their rapid greening at the onset of the monsoon, which maximizes the amount of moisture transpired from the soil into the atmosphere in the days immediately following rainfall. These ecosystems are under threat from a number of human activities, including expansion of rainfed and irrigated agriculture, deforestation for grazing activities and urbanization. These changes in land use result in dramatically different seasonality and magnitude of evapotranspiration. In this study, we examine the differences in spatial and temporal characteristics of evapotranspiration yielded by current and pre-industrial land cover. To this end, we employ the Variable Infiltration Capacity (VIC) land surface model at 1/16 degree resolution, driven by gridded meteorological observations and the MCD15A3 4-day MODIS LAI product, across the NAM region (Arizona, New Mexico, and northern Mexico). We compare the magnitude and timing of land-atmosphere fluxes given by both pre-industrial and current land cover/use, as well as the land cover under several possible alternative land use scenarios. We identify the regions where the largest changes in magnitude and timing of evapotranspiration have occurred, as well as the regions and land use changes that could produce the largest changes in future evapotranspiration under different scenarios. Finally, we explore the consequences these effects have for monsoon moisture transport.

Contribution of glomalin to dissolve organic carbon under different land uses and seasonality in dry tropics.

PubMed

Singh, Ashutosh Kumar; Rai, Apurva; Pandey, Vivek; Singh, Nandita

2017-05-01

Glomalin related soil protein (GRSP) is a hydrophobic glycoprotein that is significant for soil organic carbon (SOC) persistence and sequestration, owing to its large contribution to SOC pool and long turnover time. However, the contribution of GRSP to dissolve OC (DOC) leach from soil is not yet comprehensively explored, though it could have implication in understanding SOC dynamics. We, therefore, aim to measure the contribution of GRSP to DOC, in a range of land uses and climatic seasons in the dry tropical ecosystem. Our results demonstrated that a significant proportion of GRSP (water soluble GRSP; WS-GRSP) leached with DOC (7.9-21.9 mg kg -1 ), which accounts for 0.2-0.23% of soils total GRSP (T-GRSP). Forest exhibited significantly higher WS-GRSP and DOC leaching than fallow and agriculture. WS-GRSP and DOC accumulations were higher in the dry season (summer and winter) than in rainy. The extent of seasonal variations was higher in forest than in other two land uses, indicating the role of vegetation and biological activity in soil dissolve organic matter (DOM) dynamics. The regression analysis among WS-GRSP, T-GRSP, DOC and SOC prove that the accumulations and leaching of GRSP and other soil OM (SOM) depend on similar factors. The ratio of WS-GRSP-C to DOC was higher in agriculture soil than in forest and fallow, likely a consequence of altered soil chemistry, and organic matter quantity and quality due to soil management practices. Multivariate analysis reflects a strong linkage among GRSP and SOC storage and leaching, soil nutrients (nitrogen and phosphorus) and other important soil properties (pH and bulk density), suggesting that improving GRSP and other SOM status is an urgent need for the both SOC sequestration and soil health in dry tropical agro-ecosystems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evidence for Phanerozoic reactivation of the Najd Fault System in AVHRR, TM, and SPOT images of central Arabia

NASA Technical Reports Server (NTRS)

Andre, Constance G.

1989-01-01

SPOT stereoscopic and TM multispectral images support evidence in AVHRR thermal-IR images of a major unmapped shear zone in Phanerozoic cover rocks southeast of the ancient Najd Fault System in the Arabian Shield. This shear zone and faults of the Najd share a common alignment, orientation, and sinistral sense of movement. These similarities suggest a 200-km extension of the Najd Fault System and reactivation since it formed in the late Precambrian. Topographic and lithologic features in the TM and SPOT data along one of three faults inferred from the AVHRR data indicate sinistral offsets up to 2.5 km, en echelon folds and secondary faults like those predicted by models of left-lateral strike-slip faulting. The age of the affected outcrops indicates reactivation of Najd faults in the Cretaceous, judging from TM and SPOT data or in the Tertiary, based on AVHRR data. The total length of the system visible at the surface measures 1300 km. If the Najd Fault System is extrapolated beneath sands of the Empty Quarter to faults of a similar trend in South Yemen, the shear zone would span the Arabian Plate. Furthermore, if extensions into the Arabian Sea bed and into Egypt proposed by others are considered, it would exceed 3000 km.

Monitoring Seasonal Land Subsidence and Uplift in the Green Valley Area of the Tucson Active Management Area Groundwater Basin, Southern Arizona using Interferometric Synthetic Aperture Radar (InSAR) Data and Global Navigation Satellite System (GNSS) Data

NASA Astrophysics Data System (ADS)

Conway, B. D.

2013-12-01

The Green Valley land subsidence feature is located in southern Arizona, approximately 20 miles south of the Tucson metropolitan area within the town of Sahuarita. Groundwater levels fluctuate as much as 110 feet annually, caused by seasonal pumping demands of a nearby pecan orchard. Recent Arizona Department of Water Resources (ADWR) InSAR data and GNSS survey data reveal that seasonal land subsidence and subsequent uplift are occurring as a direct result of seasonal groundwater level fluctuations. Data from a nearby ADWR transducer shows that the groundwater level begins to decline around middle to late February, dropping as much as 110 feet by the end of June. Groundwater levels generally remain somewhat stable until the middle of October, when the groundwater level begins to rise. Groundwater levels will rise as much as 110 feet by the middle of February; a complete 12-month recovery. ADWR InSAR and GNSS survey data show that land subsidence occurs from February until May followed by a stable period, then uplift occurs from October to February. The Green Valley land subsidence feature is a dynamic hydrogeological system that requires continued deformation monitoring using both InSAR and GNSS data. Radarsat-2 Interferograms that illustrate both seasonal subsidence and uplift. Surveyed elevation and groundwater level change data that document how seasonal groundwater fluctuations result in seasonal land subsidence and uplift.

Effects of land use and seasonality on stream water quality in a small tropical catchment: The headwater of Córrego Água Limpa, São Paulo (Brazil).

PubMed

Rodrigues, Valdemir; Estrany, Joan; Ranzini, Mauricio; de Cicco, Valdir; Martín-Benito, José Mª Tarjuelo; Hedo, Javier; Lucas-Borja, Manuel E

2018-05-01

Stream water quality is controlled by the interaction of natural and anthropogenic factors over a range of temporal and spatial scales. Among these anthropogenic factors, land cover changes at catchment scale can affect stream water quality. This work aims to evaluate the influence of land use and seasonality on stream water quality in a representative tropical headwater catchment named as Córrego Água Limpa (Sao Paulo, Brasil), which is highly influenced by intensive agricultural activities and urban areas. Two systematic sampling approach campaigns were implemented with six sampling points along the stream of the headwater catchment to evaluate water quality during the rainy and dry seasons. Three replicates were collected at each sampling point in 2011. Electrical conductivity, nitrates, nitrites, sodium superoxide, Chemical Oxygen Demand (DQO), colour, turbidity, suspended solids, soluble solids and total solids were measured. Water quality parameters differed among sampling points, being lower at the headwater sampling point (0m above sea level), and then progressively higher until the last downstream sampling point (2500m above sea level). For the dry season, the mean discharge was 39.5ls -1 (from April to September) whereas 113.0ls -1 were averaged during the rainy season (from October to March). In addition, significant temporal and spatial differences were observed (P<0.05) for the fourteen parameters during the rainy and dry period. The study enhance significant relationships among land use and water quality and its temporal effect, showing seasonal differences between the land use and water quality connection, highlighting the importance of multiple spatial and temporal scales for understanding the impacts of human activities on catchment ecosystem services. Copyright © 2017 Elsevier B.V. All rights reserved.

SeaShark and Starfish opertional data processing schemes for AVHRR and SeaWiFs

NASA Astrophysics Data System (ADS)

Flowerdew, R. J.; Corlyon, Anaa M.; Greer, W. A. D.; Newby, Steve J.; Winder, C. P.

1997-02-01

SeaShark is an operational software package for processing, archiving and cataloguing AVHRR and SeaWiFS data using an operator friendly GUI. Upon receipt of a customer order, it produces standard AVHRR data products, including Sea Surface Temperature (SST) and it has recently been modified to include SeaWiFS level 2 data processing. This uses an atmospheric correction scheme developed by the Plymouth Marine Laboratory, UK (PML) that builds upon the standard Gordon and Wang approach to be applicable over both case 1 and case 2 waters. Higher level products are then generated using PML algorithms, including chlorophyll a, a CZCS-type pigment, Kd, and suspended particulate matter. Outputs are in CEOS-compatible format. The software also produces fast delivery products (FDPs) of chlorophyll a and SST. These FDPs are combined in the StarFish software package to provide maps indicating potential location of phytoplankton and the preferred thermal environment of certain pelagic fish species. Fishing vessels may obtain these maps over Inmarsat, allowing them to achieve a greater efficiency hence lower cost.

An introduction to mid-Atlantic seasonal pools

USGS Publications Warehouse

Brown, L.J.; Jung, R.E.

2005-01-01

Seasonal pools, also known as vernal ponds, provide important ecological services to the mid-Atlantic region. This publication serves as an introduction to seasonal pool ecology and management; it also provides tools for exploring seasonal pools, including a full-color field guide to wildlife. Seasonal pools are defined as having four distinctive features: surface water isolation, periodic drying, small size and shallow depth, and support of a characteristic biological community. Seasonal pools experience regular drying that excludes populations of predatory fish. Thus, pools in the mid-Atlantic region provide critical breeding habitat for amphibian and invertebrate species (e.g., spotted salamander (Ambystoma maculatum), wood frog (Rana sylvatica), and fairy shrimp (Order Anostraca)) that would be at increased risk of predation in more permanent waters. The distinctive features of seasonal pools also make them vulnerable to human disturbance. In the mid-Atlantic region, land-use changes pose the greatest challenges to seasonal pool conservation. Seasonal pools are threatened by direct loss (e.g., filling or draining of the pool) as well as by destruction and fragmentation of adjoining terrestrial habitat. Many of the species that depend on seasonal pools for breeding spend the majority of their lives in the surrounding lands that extend a radius of 1000 feet or more from the pools; these vital habitats are being transected by roads and converted to other land uses. Other threats to seasonal pools include biological introductions and removals, mosquito control practices, amphibian diseases, atmospheric deposition, and climate change. The authors recommend a three-pronged strategy for seasonal pool conservation and management in the mid-Atlantic region: education and research, inventory and monitoring of seasonal pools, and landscape-level planning and management.

Land cover characterization and land surface parameterization research

USGS Publications Warehouse

Steyaert, Louis T.; Loveland, Thomas R.; Parton, William J.

1997-01-01

The understanding of land surface processes and their parameterization in atmospheric, hydrologic, and ecosystem models has been a dominant research theme over the past decade. For example, many studies have demonstrated the key role of land cover characteristics as controlling factors in determining land surface processes, such as the exchange of water, energy, carbon, and trace gases between the land surface and the lower atmosphere. The requirements for multiresolution land cover characteristics data to support coupled-systems modeling have also been well documented, including the need for data on land cover type, land use, and many seasonally variable land cover characteristics, such as albedo, leaf area index, canopy conductance, surface roughness, and net primary productivity. Recently, the developers of land data have worked more closely with the land surface process modelers in these efforts.

Phenology of forest-grassland transition zones in the Community Land Model

NASA Astrophysics Data System (ADS)

Dahlin, K.; Fisher, R. A.

2013-12-01

Forest-grassland transition zones (savannas, woodlands, wooded grasslands, and shrublands) are highly sensitive to climate and may already be changing due to warming, changes in precipitation patterns, and/or CO2 fertilization. Shifts between closed canopy forest and open grassland, as well as shifts in phenology, could have large impacts on the global carbon cycle, water balance, albedo, and on the humans and other animals that depend on these regions. From an earth system perspective these impacts may then feed back into the climate system and impact how, when, and where climate change occurs. Here we compare 29 years of monthly leaf area index (LAI) outputs from several offline versions of the Community Land Model (CLM), the land component of the Community Earth System Model, to LAI derived from the AVHRR NDVI3g product (LAI3g). Specifically, we focus on seasonal patterns in regions dominated by tropical broadleaved deciduous trees (T-BDT), broadleaved deciduous shrubs (BDS) and grasslands (C3 and C4) in CLM, all of which follow a 'stress deciduous' phenological algorithm. We consider and compare two versions of CLM (v. 4CN and v. 4.5BGC) to the satellite derived product. We found that both versions of CLM were able to capture seasonal variations in grasslands relatively well at the regional scale, but that the 'stress deciduous' phenology algorithm did not perform well in areas dominated by T-BDT or BDS. When we compared the performance of the models at single points we found slight improvements in CLM4.5BGC over CLM4CN, but generally that the magnitude of seasonality was too low in CLM as compared to the LAI3g satellite product. To explore the parameters within CLM that had the most leverage on seasonality of LAI, we used a Latin hypercube approach to vary values for critical soil water potential (threshold at which plants drop leaves), the critical number of days that soil water potential must be too low for leaves to drop, and the carbon allocation scheme

Land Cover Influence on Wet Season Storm Runoff Generation and Hydrologic Flowpaths in Central Panama

NASA Astrophysics Data System (ADS)

Birch, A. L.; Stallard, R. F.; Barnard, H. R.

2017-12-01

While relationships between land use/land cover and hydrology are well studied and understood in temperate parts of the world, little research exists in the humid tropics, where hydrologic research is often decades behind. Specifically, quantitative information on how physical and biological differences across varying land covers influence runoff generation and hydrologic flowpaths in the humid tropics is scarce; frequently leading to poorly informed hydrologic modelling and water policy decision making. This research effort seeks to quantify how tropical land cover change may alter physical hydrologic processes in the economically important Panama Canal Watershed (Republic of Panama) by separating streamflow into its different runoff components using end member mixing analysis. The samples collected for this project come from small headwater catchments of four varying land covers (mature tropical forest, young secondary forest, active pasture, recently clear-cut tropical forest) within the Smithsonian Tropical Research Institute's Agua Salud Project. During the past three years, samples have been collected at the four study catchments from streamflow and from a number of water sources within hillslope transects, and have been analyzed for stable water isotopes, major cations, and major anions. Major ion analysis of these samples has shown distinct geochemical differences for the potential runoff generating end members sampled (soil moisture/ preferential flow, groundwater, overland flow, throughfall, and precipitation). Based on this finding, an effort was made from May-August 2017 to intensively sample streamflow during wet season storm events, yielding a total of 5 events of varying intensity in each land cover/catchment, with sampling intensity ranging from sub-hourly to sub-daily. The focus of this poster presentation will be to present the result of hydrograph separation's done using end member mixing analysis from this May-August 2017 storm dataset. Expected

Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery

NASA Technical Reports Server (NTRS)

Estes, John E.; Gebelein, Jennifer

1999-01-01

This report is produced in accordance with the requirements outlined in the NASA Research Grant NAG9-1032 titled "Validation of Land Cover Maps Utilizing Astronaut Acquired Imagery". This grant funds the Remote Sensing Research Unit of the University of California, Santa Barbara. This document summarizes the research progress and accomplishments to date and describes current on-going research activities. Even though this grant has technically expired, in a contractual sense, work continues on this project. Therefore, this summary will include all work done through and 5 May 1999. The principal goal of this effort is to test the accuracy of a sub-regional portion of an AVHRR-based land cover product. Land cover mapped to three different classification systems, in the southwestern United States, have been subjected to two specific accuracy assessments. One assessment utilizing astronaut acquired photography, and a second assessment employing Landsat Thematic Mapper imagery, augmented in some cases, high aerial photography. Validation of these three land cover products has proceeded using a stratified sampling methodology. We believe this research will provide an important initial test of the potential use of imagery acquired from Shuttle and ultimately the International Space Station (ISS) for the operational validation of the Moderate Resolution Imaging Spectrometer (MODIS) land cover products.

Monthly fractional green vegetation cover associated with land cover classes of the conterminous USA

USGS Publications Warehouse

Gallo, Kevin P.; Tarpley, Dan; Mitchell, Ken; Csiszar, Ivan; Owen, Timothy W.; Reed, Bradley C.

2001-01-01

The land cover classes developed under the coordination of the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) have been analyzed for a study area that includes the Conterminous United States and portions of Mexico and Canada. The 1-km resolution data have been analyzed to produce a gridded data set that includes within each 20-km grid cell: 1) the three most dominant land cover classes, 2) the fractional area associated with each of the three dominant classes, and 3) the fractional area covered by water. Additionally, the monthly fraction of green vegetation cover (fgreen) associated with each of the three dominant land cover classes per grid cell was derived from a 5-year climatology of 1-km resolution NOAA-AVHRR data. The variables derived in this study provide a potential improvement over the use of monthly fgreen linked to a single land cover class per model grid cell.

Glycolytic adjustments in tissues of frog Rana ridibunda and land snail Helix lucorum during seasonal hibernation.

PubMed

Michaelidis, Basile; Kyriakopoulou-Sklavounou, Pasqualina; Staikou, Alexandra; Papathanasiou, Ioanna; Konstantinou, Kiriaki

2008-12-01

The present work aimed to contribute to the understanding of the adaptation of the glycolytic pathway in tissues of frog Rana ridibunda and land snail species Helix lucorum during seasonal hibernation. Moreover responses of glycolytic enzymes from cold acclimated R. ridibunda and H. lucorum were studied as well. The drop in Po(2) in the blood of hibernated frogs and land snails indicated lower oxygen consumption and a decrease in their metabolic rate. The activities of glycolytic enzymes indicated that hibernation had a differential effect on the glycolyis in the two species studied and also in the tissues of the same species. The activity of l-LDH decreased significantly in the skeletal muscle and heart of hibernated R. ridibunda indicating a low glycolytic potential. Similar biochemical responses were observed in the same tissues during cold acclimation. The continuous increase in the activities of glycolytic enzymes studied, except for HK, might indicate a compensation for the impacts of low temperature on the enzymatic activities. In contrast to R. ridibunda, the activities of the enzymes increased and remained at higher levels than those of the prehibernation controls indicating maintenance of glycolytic potential in the tissues of hibernating land snails.

Mapping Land Cover Types in Amazon Basin Using 1km JERS-1 Mosaic

NASA Technical Reports Server (NTRS)

Saatchi, Sassan S.; Nelson, Bruce; Podest, Erika; Holt, John

2000-01-01

In this paper, the 100 meter JERS-1 Amazon mosaic image was used in a new classifier to generate a I km resolution land cover map. The inputs to the classifier were 1 km resolution mean backscatter and seven first order texture measures derived from the 100 m data by using a 10 x 10 independent sampling window. The classification approach included two interdependent stages: 1) a supervised maximum a posteriori Bayesian approach to classify the mean backscatter image into 5 general land cover categories of forest, savannah, inundated, white sand, and anthropogenic vegetation classes, and 2) a texture measure decision rule approach to further discriminate subcategory classes based on taxonomic information and biomass levels. Fourteen classes were successfully separated at 1 km scale. The results were verified by examining the accuracy of the approach by comparison with the IBGE and the AVHRR 1 km resolution land cover maps.

Interannual Variations in Global Vegetation Phenology Derived from a Long Term AVHRR and MODIS Data Record

NASA Astrophysics Data System (ADS)

Zhang, X.; Friedl, M. A.; Yu, Y.

2013-12-01

Land surface phenology metrics are widely retrieved from satellite observations at regional and global scales, and have been shown to be valuable for monitoring terrestrial ecosystem dynamics in response to extreme climate events and predicting biological responses to future climate scenarios. While the response of spring vegetation greenup to climate warming at mid-to-high latitudes is well-documented, understanding of diverse phenological responses to climate change over entire growing cycles and at broad geographic scales is incomplete. Many studies assume that the timing of individual phenological indicators in responses to climate forcing is independent of phenological events that occur at other times during the growing season. In this paper we use a different strategy. Specifically, we hypothesize that integrating sequences of key phenological indicators across growing seasons provides a more effective way to capture long-term variation in phenology in response to climate change. To explore this hypothesis we use global land surface phenology metrics derived from the Version 3 Long Term Vegetation Index Products from Multiple Satellite Data Records data set to examine interannual variations and trends in global land surface phenology from 1982-2010. Using daily enhanced vegetation index (EVI) data at a spatial resolution of 0.05 degrees, we model the phenological trajectory for each individual pixel using piecewise logistic models. The modeled trajectories were then used to detect phenological indicators including the onset of greenness increase, the onset of greenness maximum, the onset of greenness decrease, the onset of greenness minimum, and the growing season length, among others at global scale. The quality of land surface phenology detection for individual pixels was calculated based on metrics that characterize the EVI quality and model fits in annual time series at each pixel. Phenological indicators characterized as having good quality were then

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

USGS Publications Warehouse

Saunders, Sarah P.; Ries, Leslie; Oberhasuer, Karen S.; Thogmartin, Wayne E.; Zipkin, Elise F.

2017-01-01

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

1984-01-01

Multivariate statistical analysis and imaging processing techniques are being applied to the study of arid/semiarid environments, with emphasis on desertification. Field level indicators of land-soil biota degradation are being sifted out with staging up to the low aircraft reconnaissance level, to LANDSAT TM & MSS, and even to the AVHRR level. Three completed projects are reviewed: riparian habitat on the Humboldt River floodplain, Salt Lake County Urban expansion detection, and salinization/desertification detection in the delta area. Beginning projects summarized include: comparative condition of rangeland in Rush Valley; modeling a GIS/remote sensing data base for Cache County; universal soil loss equation applied to Pinyon-Juniper; relating MSS to ground radiometry near Battle Mountain; and riparian habitat mapping on Mary's River, Nevada.

Lake surface water temperatures of European Alpine lakes (1989-2013) based on the Advanced Very High Resolution Radiometer (AVHRR) 1 km data set

NASA Astrophysics Data System (ADS)

Riffler, M.; Lieberherr, G.; Wunderle, S.

2015-02-01

Lake water temperature (LWT) is an important driver of lake ecosystems and it has been identified as an indicator of climate change. Consequently, the Global Climate Observing System (GCOS) lists LWT as an essential climate variable. Although for some European lakes long in situ time series of LWT do exist, many lakes are not observed or only on a non-regular basis making these observations insufficient for climate monitoring. Satellite data can provide the information needed. However, only few satellite sensors offer the possibility to analyse time series which cover 25 years or more. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown as a heritage instrument for almost 35 years. It will be carried on for at least ten more years, offering a unique opportunity for satellite-based climate studies. Herein we present a satellite-based lake surface water temperature (LSWT) data set for European water bodies in or near the Alps based on the extensive AVHRR 1 km data record (1989-2013) of the Remote Sensing Research Group at the University of Bern. It has been compiled out of AVHRR/2 (NOAA-07, -09, -11, -14) and AVHRR/3 (NOAA-16, -17, -18, -19 and MetOp-A) data. The high accuracy needed for climate related studies requires careful pre-processing and consideration of the atmospheric state. The LSWT retrieval is based on a simulation-based scheme making use of the Radiative Transfer for TOVS (RTTOV) Version 10 together with ERA-interim reanalysis data from the European Centre for Medium-range Weather Forecasts. The resulting LSWTs were extensively compared with in situ measurements from lakes with various sizes between 14 and 580 km2 and the resulting biases and RMSEs were found to be within the range of -0.5 to 0.6 K and 1.0 to 1.6 K, respectively. The upper limits of the reported errors could be rather attributed to uncertainties in the data comparison between in situ and satellite observations than inaccuracies of the satellite

[Variability of vegetation growth season in different latitudinal zones of North China: a monitoring by NOAA NDVI and MSAVI].

PubMed

Wang, Hong; Li, Xiaobing; Han, Ruibo; Ge, Yongqin

2006-12-01

In this study, North China was latitudinally divided into five zones, i.e., 32 degrees - 36 degrees N (Zone I), 36 degrees - 40 degrees N (Zone II), 40 degrees - 44 degrees N (Zone III), 44 degrees - 48 degrees N (Zone IV) and 48 degrees - 52 degrees N (Zone V), and the NOAA/ AVHRR NDVI and MSAVI time-series images from 1982 to 1999 were smoothed with Savitzky-Golay filter algorithm. Based on the EOF analysis, the principal components of NDVI and MSAVI for the vegetations in different latitudinal zones of North China were extracted, the annual beginning and ending dates and the length of growth season in 1982 - 1999 were estimated, and the related parameters were linearly fitted, aimed to analyze the variability of vegetation growth season. The results showed that the beginning date of the growth season in different zones tended to be advanced, while the ending date tended to be postponed with increasing latitude. The length of the growth season was also prolonged, with the prolonging time exceeded 10 days.

Seasonal Biophysical Dynamics of the Amazon from Space Using MODIS Vegetation Indices

NASA Astrophysics Data System (ADS)

Huete, A. R.; Didan, K.; Ratana, P.; Ferreira, L.

2002-12-01

We utilized the Terra- Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index (VI) products to analyze the seasonal and spatial patterns of photosynthetic vegetation activity over the Amazon Basin and surrounding regions of Brazil. The seasonal patterns of vegetation activity were studied along two, eco-climatic transects extending from (1) the cerrado region (Brasilia National Park) to the seasonal tropical forest (Tapajos National Forest) and (2) the caatinga biome to the seasonal and per-humid tropical forests. In addition to the climatic transects, we also investigated the seasonal dynamics of altered, land conversion areas associated with pastures and clearcutting land use activities. Both the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) at 250-m, 500-m, and 1-km were used to extract seasonal profile curves. The quality assurance (QA) information of the output products was used in noise removal and data filtering prior to the generation of the seasonal profiles. Histogram analyses were also performed at coarse (biome) scale and fine, site intensive (flux towers) scale. The seasonal patterns of the cerrado and caatinga were very pronounced with distinct dry and wet seasonal trends. We observed decreasing dry-wet seasonal patterns in the transitional areas near Araguaia National Park. In contrast, the seasonal behavior of the tropical forests were much harder to assess, but indicated slight seasonal trends that ran counter to rainfall activity. This may be attributed to new leaf growth in the dry season. We further found MODIS VI seasonal patterns to vary significantly in land converted and land degraded areas.

Interactive visualization of vegetation dynamics

USGS Publications Warehouse

Reed, B.C.; Swets, D.; Bard, L.; Brown, J.; Rowland, James

2001-01-01

Satellite imagery provides a mechanism for observing seasonal dynamics of the landscape that have implications for near real-time monitoring of agriculture, forest, and range resources. This study illustrates a technique for visualizing timely information on key events during the growing season (e.g., onset, peak, duration, and end of growing season), as well as the status of the current growing season with respect to the recent historical average. Using time-series analysis of normalized difference vegetation index (NDVI) data from the advanced very high resolution radiometer (AVHRR) satellite sensor, seasonal dynamics can be derived. We have developed a set of Java-based visualization and analysis tools to make comparisons between the seasonal dynamics of the current year with those from the past twelve years. In addition, the visualization tools allow the user to query underlying databases such as land cover or administrative boundaries to analyze the seasonal dynamics of areas of their own interest. The Java-based tools (data exploration and visualization analysis or DEVA) use a Web-based client-server model for processing the data. The resulting visualization and analysis, available via the Internet, is of value to those responsible for land management decisions, resource allocation, and at-risk population targeting.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

Application of AVHRR vegetation index to study atmosphere-biosphere exchange of CO2: Results from a 3-D tracer transport model

NASA Technical Reports Server (NTRS)

Fung, Inez Y.; Tucker, C. J.; Prentice, Katharine C.

1985-01-01

The 'normalized difference vegetation indices' (NVI) derived from AVHRR radiances are combined with field data of soil respiration and a global map of net primary productivity to prescribe, for the globe, the seasonal exchange of CO2 between the atmosphere and the terrestrial biosphere. The monthly fluxes of CO2 thus obtained are used as inputs to a 3-D tracer transport model which uses winds generated by a 3-D atmospheric general circulation model to advect CO2 as an inert constituent. Analysis of the 3-D model results shows reasonable agreement between the simulated and observed annual cycles of atmospheric CO2 at the locations of the remote monitoring stations. The application is shown of atmospheric CO2 distributions to calibrate the NVI in terms of carbon fluxes. The approach suggests that the NVI may be used to provide quantitative information about long term and global scale variations of photosynthetic activity and of atmospheric CO2 concentrations provided that variations in the atmospheric circulation and in atmospheric composition are known.

Iron, manganese and phosphorus partitioning during high flow events: impacts of land cover and seasonality

NASA Astrophysics Data System (ADS)

Schroth, A. W.

2015-12-01

Metals and phosphorous are essential micro and macronutrients in aquatic ecosystems, and redox sensitive colloidal and particulate metal (oxy)hydroxide phases can be particularly reactive carriers of solid phase P, as well as other nutrients and/or pollutants in riverine chemical loads. High flow events driven by storms and/or snow or glacial melt often dominate the annual load of such constituents, yet remain poorly understood from a biogeochemical perspective. Our research examines the biogeochemical nature of riverine metal and P loads during targeted high flow events to determine to what extent, and under what environmental conditions, are the concentration and biogeochemical composition of riverine loads of P, Fe, and Mn disproportionately high and relatively reactive v. inert. We present a suite of biogeochemical data derived from water and suspended sediment samples that were collected during these events in multiple catchments and over different seasons within the hydrologic year. We examine the size partitioning (particulate, colloidal, 'truly dissolved') of riverine Fe, Mn, and P during events in glaciated, boreal-forested, and agriculturalized catchments of Vermont and Alaska. Suspended sediment loads are also characterized by relative redox sensitivity to examine the potential reactivity of Fe, Mn, and P in sediment transported during particular events. We demonstrate that metal and P concentration, size partitioning, and redox sensitivity differs both seasonally and by land cover, which is due to different source environments and flow paths that are preferentially activated during high discharge. The conceptual model herein developed is critical to understanding the biogeochemical nature of event-based riverine loads, and how this could evolve with changing frequency and severity of high flow events or land cover associated with climate change and landscape management.

Land cover mapping of Greater Mesoamerica using MODIS data

USGS Publications Warehouse

Giri, Chandra; Jenkins, Clinton N.

2005-01-01

A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.

The Circumpolar Arctic Vegetation Map: AVHRR-derived base maps, environmental controls, and integrated mapping procedures

Treesearch

D. A. WALKER; W. A. GOULD; MAIERH. A.; M. K. RAYNOLDS

2002-01-01

A new false-colour-infrared image derived from biweekly 1993 and 1995 Advanced Very High Resolution Radiometer (AVHRR) data provides a snow-free and cloud-free base image for the interpretation of vegetation as part of a 1:7.5M-scale Circumpolar Arctic Vegetation Map (CAVM). A maximum-NDVI (Normalized DiVerence Vegetation Index) image prepared from the same data...

The impact of land use and season on the riverine transport of mercury into the marine coastal zone.

PubMed

Saniewska, Dominika; Bełdowska, Magdalena; Bełdowski, Jacek; Saniewski, Michał; Szubska, Marta; Romanowski, Andrzej; Falkowska, Lucyna

2014-11-01

In Mediterranean seas and coastal zones, rivers can be the main source of mercury (Hg). Catchment management therefore affects the load of Hg reaching the sea with surface runoff. The major freshwater inflows to the Baltic Sea consist of large rivers. However, their systems are complex and identification of factors affecting the outflow of Hg from its catchments is difficult. For this reason, a study into the impact of watershed land use and season on mercury biogeochemistry and transport in rivers was performed along two small rivers which may be considered typical of the southern Baltic region. Neither of these rivers are currently impacted by industrial effluents, thus allowing assessment of the influence of catchment terrain and season on Hg geochemistry. The study was performed between June 2008 and May 2009 at 13 sampling points situated at different terrain types within the catchments (forest, wetland, agriculture and urban). Hg analyses were conducted by CVAFS. Arable land erosion was found to be an important source of Hg to the aquatic system, similar to urban areas. Furthermore, inflows of untreated storm water discharge resulted in a fivefold increase of Hg concentration in the rivers. The highest Hg concentration in the urban runoff was observed with the greatest amount of precipitation during summer. Moderate rainfalls enhance the inflow of bioavailable dissolved mercury into water bodies. Despite the lack of industrial effluents entering the rivers directly, the sub-catchments with anthropogenic land use were important sources of Hg in the rivers. This was caused by elution of metal, deposited in soils over the past decades, into the rivers. The obtained results are especially important in the light of recent environmental conscience regulations, enforcing the decrease of pollution by Baltic countries.

Seasonal Forecasting of Fires across Southern Borneo, 1997-2010

NASA Astrophysics Data System (ADS)

Spessa, Allan; Field, Robert; Kaiser, Johannes; Langner, Andreas; Moore, Jonathan; Pappenberger, Florian; Siegert, Florian; Weber, Ulrich

2014-05-01

several studies using historical data have established negative relationships between fires and antecedent rainfall, and/or positive relationships between fires and deforestation in regions affected by El Nino, comparatively little work has attempted to predict fires and emissions in such regions. Ensemble seasonal climate forecasts issued with several months lead-time have been applied to support risk assessment systems in many fields, notably agricultural production and natural disaster management of flooding, heat waves, drought and fire. The USA, for example, has a long-standing seasonal fire danger prediction system. Fire danger monitoring systems have been operating in Indonesia for over a decade, but, as of yet, no fire danger prediction systems exist. Given the effort required to mobilise suppression and prevention measures in Indonesia, one could argue that high fire danger periods must be anticipated months in advance for mitigation and response measures to be effective. To address this need, the goal of our work was to examine the utility of seasonal rainfall forecasts in predicting severe fires in Indonesia more than one month in advance, using southern Borneo (comprising the bulk of Kalimantan) as a case study. Here we present the results of comparing seasonal forecasts of monthly rainfall from ECMWF's System 4 against i) observed rainfall (GPCP), and ii) burnt area and deforestation (MODIS, AVHRR and Landsat) across southern Borneo for the period 1997-2010. Our results demonstrate the utility of using ECMWF's seasonal climate forecasts for predicting fire activity in the region. Potential applications include improved fire mitigation and responsiveness, and improved risk assessments of biodiversity and carbon losses through fire. These are important considerations for forest protection programmes (e.g. REDD+), forest carbon markets and forest (re)insurance enterprises.

A Comparison of Various Estimators for Updating Forest Area Coverage Using AVHRR and Forest Inventory Data

Treesearch

Francis A. Roesch; Paul C. van Deusen; Zhiliang Zhu

1995-01-01

Various methods of adjusting low-cost and possibly biased estimates of percent forest coverage from AVHRR data with a subsample of higher-cost estimates from the USDA Forest Service's Forest Inventory and Analysis plots were investigated. Two ratio and two regression estimators were evaluated. Previous work (Zhu and Teuber, 1991) finding that the estimates from...

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

Nizamuddin, Mohammad; Akhand, Kawsar; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

Quantification of Surface Suspended Sediments along a River Dominated Coast with NOAA AVHRR and SeaWiFS Measurements: Louisiana, USA

NASA Technical Reports Server (NTRS)

Myint, S. W.; Walker, N. D.

2002-01-01

The ability to quantify suspended sediment concentrations accurately over both time and space using satellite data has been a goal of many environmental researchers over the past few decades This study utilizes data acquired by the NOAA Advanced Very High Resolution Radiometer (AVHRR) and the Orbview-2 Sea-viewing wide field-of-view (SeaWiFS) ocean colour sensor, coupled with field measurements to develop statistical models for the estimation of near-surface suspended sediment and suspended solids "Ground truth" water samples were obtained via helicopter, small boat and automatic water sampler within a few hours of satellite overpasses The NOAA AVHRR atmospheric correction was modified for the high levels of turbidity along the Louisiana coast. Models were developed based on the field measurements and reflectance/radiance measurements in the visible and near infrared Channels of NOAA-14 and Orbview-2 SeaWiFS. The best models for predicting surface suspended sediment concentrations were obtained with a NOAA AVHRR Channel 1 (580-680nm) cubic model, Channel 2 (725-1100 nm) linear mod$ and SeaWiFs Channel 6 (660-68Onm) power modeL The suspended sediment models developed using SeaWiFS Channel 5 (545-565 nm) were inferior, a result that we attribute mainly to the atmospheric correction technique, the shallow depth of the water samples and absorption effects from non-sediment water constituents.

Mosquito communities and disease risk influenced by land use change and seasonality in the Australian tropics.

PubMed

Meyer Steiger, Dagmar B; Ritchie, Scott A; Laurance, Susan G W

2016-07-07

Anthropogenic land use changes have contributed considerably to the rise of emerging and re-emerging mosquito-borne diseases. These diseases appear to be increasing as a result of the novel juxtapositions of habitats and species that can result in new interchanges of vectors, diseases and hosts. We studied whether the mosquito community structure varied between habitats and seasons and whether known disease vectors displayed habitat preferences in tropical Australia. Using CDC model 512 traps, adult mosquitoes were sampled across an anthropogenic disturbance gradient of grassland, rainforest edge and rainforest interior habitats, in both the wet and dry seasons. Nonmetric multidimensional scaling (NMS) ordinations were applied to examine major gradients in the composition of mosquito and vector communities. We captured ~13,000 mosquitoes from 288 trap nights across four study sites. A community analysis identified 29 species from 7 genera. Even though mosquito abundance and richness were similar between the three habitats, the community composition varied significantly in response to habitat type. The mosquito community in rainforest interiors was distinctly different to the community in grasslands, whereas forest edges acted as an ecotone with shared communities from both forest interiors and grasslands. We found two community patterns that will influence disease risk at out study sites, first, that disease vectoring mosquito species occurred all year round. Secondly, that anthropogenic grasslands adjacent to rainforests may increase the probability of novel disease transmission through changes to the vector community on rainforest edges, as most disease transmitting species predominantly occurred in grasslands. Our results indicate that the strong influence of anthropogenic land use change on mosquito communities could have potential implications for pathogen transmission to humans and wildlife.

Analyzing vegetation dynamics of land systems with satellite data

USGS Publications Warehouse

Eidenshink, Jeffery C.; Haas, Robert H.

1992-01-01

Large area assessment of vegetation conditions is a major requirement for understanding the impact of weather on food, fiber, and forage production. The distribution of vegetation is largely associated with climate, terrain characteristics, and human activity. The interpretation of vegetation dynamics from satellite data can be improved by stratifying the land surface into ecoregions. The Soil Conservation Service, U.S. Department of Agriculture, has developed a system for mapping major land resource areas (MLRA) that groups land areas in the United States on the basis of climate, physiography, land use, and land cover characteristics.In 1989, the U.S. Geological Survey used National Oceanic and Atmospheric Administration weather satellite data to conduct a biweekly assessment of vegetation conditions in 17 western states. Advanced Very High Resolution Radiometer data were acquired daily, and were geographically registered, and the normalized difference vegetation index (NDVI) was computed for the Western United States during the 1989 growing season. Fifteen biweekly NDVI data sets were used to evaluate MLRA's as an appropriate stratification for monitoring and interpreting vegetation conditions in the study area.The results demonstrate the feasibility of using MLRA's to stratify areas for monitoring phenological development and vegetation condition assessment within the growing season. Assessments of the NDVI at biweekly intervals are adequate for monitoring seasonal growth patterns on MLRA's where rangelands, forests, or cultivated agriculture are the primary resource type. Descriptive statistics are indicators of the uniformity or diversity of land use and land cover within an MLRA. Growing season profiles of the NDVI are characterized by the seasonal effects of climate on various land use and land cover classes.

Monthly and seasonal variability of the land-atmosphere system

Treesearch

Yong-Qiang Liu

2003-01-01

The land surface and the atmosphere can interact with each other through exchanges of energy, water, and momentum. With the capacity of long memory, land surface processes can contribute to long-term variability of atmospheric processes. Great efforts have been made in the past three decades to study land-atmosphere interactions and their importance to long-term...

A Local Forecast of Land Surface Wetness Conditions, Drought, and St. Louis Encephalitis Virus Transmission Derived from Seasonal Climate Predictions

NASA Astrophysics Data System (ADS)

Shaman, J.; Stieglitz, M.; Zebiak, S.; Cane, M.; Day, J. F.

2002-12-01

We present an ensemble local hydrologic forecast derived from the seasonal forecasts of the International Research Institute (IRI) for Climate Prediction. Three- month seasonal forecasts were used to resample historical meteorological conditions and generate ensemble forcing datasets for a TOPMODEL-based hydrology model. Eleven retrospective forecasts were run at a Florida and New York site. Forecast skill was assessed for mean area modeled water table depth (WTD), i.e. near surface soil wetness conditions, and compared with WTD simulated with observed data. Hydrology model forecast skill was evident at the Florida site but not at the New York site. At the Florida site, persistence of hydrologic conditions and local skill of the IRI seasonal forecast contributed to the local hydrologic forecast skill. This forecast will permit probabilistic prediction of future hydrologic conditions. At the Florida site, we have also quantified the link between modeled WTD (i.e. drought) and the amplification and transmission of St. Louis Encephalitis virus (SLEV). We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission associated with human clinical cases. We then combine the seasonal forecasts of local, modeled WTD with this empirical relationship and produce retrospective probabilistic seasonal forecasts of epidemic SLEV transmission in Florida. Epidemic SLEV transmission forecast skill is demonstrated. These findings will permit real-time forecast of drought and resultant SLEV transmission in Florida.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

NASA Astrophysics Data System (ADS)

Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

2018-03-01

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

A spatial regression procedure for evaluating the relationship between AVHRR-NDVI and climate in the northern Great Plains

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

The relationship between vegetation and climate in the grassland and cropland of the northern US Great Plains was investigated with Normalized Difference Vegetation Index (NDVI) (1989–1993) images derived from the Advanced Very High Resolution Radiometer (AVHRR), and climate data from automated weather stations. The relationship was quantified using a spatial regression technique that adjusts for spatial autocorrelation inherent in these data. Conventional regression techniques used frequently in previous studies are not adequate, because they are based on the assumption of independent observations. Six climate variables during the growing season; precipitation, potential evapotranspiration, daily maximum and minimum air temperature, soil temperature, solar irradiation were regressed on NDVI derived from a 10-km weather station buffer. The regression model identified precipitation and potential evapotranspiration as the most significant climatic variables, indicating that the water balance is the most important factor controlling vegetation condition at an annual timescale. The model indicates that 46% and 24% of variation in NDVI is accounted for by climate in grassland and cropland, respectively, indicating that grassland vegetation has a more pronounced response to climate variation than cropland. Other factors contributing to NDVI variation include environmental factors (soil, groundwater and terrain), human manipulation of crops, and sensor variation.

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

NASA Technical Reports Server (NTRS)

Potter, C. S.; Brooks, V.

1997-01-01

This paper describes the use of satellite data to calibrate a new climate-vegetation greenness relationship for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes If the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980's in order to refine our understanding of intra-annual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global 1o gridded data sets suggest that three climate indexes: degree days (growing/chilling), annual precipitation total, and an annual moisture index together can account to 70-80 percent of the geographic variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same annual climate index values from the previous year explains no substantial additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes is closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from lo grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI for several different years at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes are not accurately predicted are mainly high latitude zones, mixed and disturbed vegetation types, and other remote locations where climate station data are sparse.

Simulations of the general circulation of the Martian atmosphere. II - Seasonal pressure variations

NASA Technical Reports Server (NTRS)

Pollack, James B.; Haberle, Robert M.; Murphy, James R.; Schaeffer, James; Lee, Hilda

1993-01-01

The CO2 seasonal cycle of the Martian atmosphere and surface is simulated with a hybrid energy balance model that incorporates dynamical and radiation information from a large number of general circulation model runs. This information includes: heating due to atmospheric heat advection, the seasonally varying ratio of the surface pressure at the two Viking landing sites to the globally averaged pressure, the rate of CO2 condensation in the atmosphere, and solar heating of the atmosphere and surface. The predictions of the energy balance model are compared with the seasonal pressure variations measured at the two Viking landing sites and the springtime retreat of the seasonal polar cap boundaries. The following quantities are found to have a strong influence on the seasonal pressures at the Viking landing sites: albedo of the seasonal CO2 ice deposits, emissivity of this deposit, atmospheric heat advection, and the pressure ratio.

Evaluating operational AVHRR sea surface temperature data at the coastline using surfers

NASA Astrophysics Data System (ADS)

Brewin, Robert J. W.; de Mora, Lee; Billson, Oliver; Jackson, Thomas; Russell, Paul; Brewin, Thomas G.; Shutler, Jamie D.; Miller, Peter I.; Taylor, Benjamin H.; Smyth, Tim J.; Fishwick, James R.

2017-09-01

Sea surface temperature (SST) is an essential climate variable that can be measured routinely from Earth Observation (EO) with high temporal and spatial coverage. To evaluate its suitability for an application, it is critical to know the accuracy and precision (performance) of the EO SST data. This requires comparisons with co-located and concomitant in situ data. Owing to a relatively large network of in situ platforms there is a good understanding of the performance of EO SST data in the open ocean. However, at the coastline this performance is not well known, impeded by a lack of in situ data. Here, we used in situ SST measurements collected by a group of surfers over a three year period in the coastal waters of the UK and Ireland, to improve our understanding of the performance of EO SST data at the coastline. At two beaches near the city of Plymouth, UK, the in situ SST measurements collected by the surfers were compared with in situ SST collected from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected by the surfers around the coastline, and those collected offshore by the two autonomous buoys, were used to evaluate the performance of operational Advanced Very High Resolution Radiometer (AVHRR) EO SST data. Results indicate: (i) a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square errors in the range of 1.0 to 2.0 °C depending on the temporal difference between match-ups, significantly higher than those at the two offshore stations (0.4 to 0.6 °C); (ii) a systematic negative bias in the AVHRR retrievals of approximately 1 °C at the coastline, not observed at the two offshore stations; and (iii) an increase in the root mean square error at the coastline when the temporal difference between match-ups exceeded three hours. Harnessing new solutions

Agro-pastoral expansion and land use/land cover (LU/LC) change dynamics in Central-western Brazil

NASA Astrophysics Data System (ADS)

Sanga-Ngoie, K.; Yoshikawa, S.; Kanae, S.

2011-12-01

In Brazil, large-scale land cover changes following extensive deforestations are expected to generate big impacts onto the climate and the environment over this area, with eventually many negative feedbacks on the global scale. Mato Grosso State, located in the central western Brazil, is known to be the Brazilian state with the highest deforestation rate. Land use/land cover (LU/LC) changes have been reported to occur over large areas in this state due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. In this study, we specifically aim at doing more detailed analysis for the causes of deforestation and savannization in this area, with special attention to agriculture and cattle ranching industry at the municipal district level in this state. Using GIS techniques and remotely-sensed NOAA/AVHRR data, we created 5-year Digital Vegetation Model Maps characterizing LU/LC features for every five years during the 1981-2001 periods using the PCA first components of the NOAA/AVHRR multi-spectral data. Our results make it clear that: (1) LU/LC changes among the phases are of the following 3 major types: degradation, recovery or transition; (2) The changes in LU/LC features are concomitant with the advance of cattle ranching and corn production activities toward the northern parts of the state, and with the expansion of soybean production in the central and western Mato Grosso; (3) Most of the agro-pastoral business are found in the southern Mato Grosso where about 46% of the state's deforestation during the 1981-2001 period occurred; (4) Rates of vegetation change are larger over non-inhabited areas (56%), especially in the north, than over the populated zones in the south (42%). Moreover, this work sheds some new light on the patterns of the changes in LU/LC features (deforestation and savannization) for each municipal district of Mato Grosso. In general, the following activities

Evaluating Impacts of climate and land use changes on streamflow using SWAT and land use models based CESM1-CAM5 Climate scenarios

NASA Astrophysics Data System (ADS)

Lin, Tzu Ping; Lin, Yu Pin; Lien, Wan Yu

2015-04-01

Climate change projects have various levels of impacts on hydrological cycles around the world. The impact of climate change and uncertainty of climate projections from general circulation models (GCMs) from the Coupled Model Intercomparison Project (CMIP5) which has been just be released in Taiwan, 2014. Since the streamflow run into ocean directly due to the steep terrain and the rainfall difference between wet and dry seasons is apparent; as a result, the allocation water resource reasonable is very challenge in Taiwan, particularly under climate change. The purpose of this study was to evaluate the impacts of climate and land use changes on a small watershed in Taiwan. The AR5 General Circulation Models(GCM) output data was adopted in this study and was downscaled from the monthly to the daily weather data as the input data of hydrological model such as Soil and Water Assessment Tool (SWAT) model in this study. The spatially explicit land uses change model, the Conservation of Land Use and its Effects at Small regional extent (CLUE-s), was applied to simulate land use scenarios in 2020-2039. Combined climate and land use change scenarios were adopted as input data of the hydrological model, the SWAT model, to estimate the future streamflows. With the increasing precipitation, increasing urban area and decreasing agricultural and grass land, the annual streamflow in the most of twenty-three subbasins were also increased. Besides, due to the increasing rainfall in wet season and decreasing rainfall in dry season, the difference of streamflow between wet season and dry season are also increased. This result indicates a more stringent challenge on the water resource management in future. Therefore, impacts on water resource caused by climate change and land use change should be considered in water resource planning for the Datuan river watershed. Keywords: SWAT, GCM, CLUE-s, streamflow, climate change, land use change

Study on Remote Sensing Image Characteristics of Ecological Land: Case Study of Original Ecological Land in the Yellow River Delta

NASA Astrophysics Data System (ADS)

An, G. Q.

2018-04-01

Takes the Yellow River Delta as an example, this paper studies the characteristics of remote sensing imagery with dominant ecological functional land use types, compares the advantages and disadvantages of different image in interpreting ecological land use, and uses research results to analyse the changing trend of ecological land in the study area in the past 30 years. The main methods include multi-period, different sensor images and different seasonal spectral curves, vegetation index, GIS and data analysis methods. The results show that the main ecological land in the Yellow River Delta included coastal beaches, saline-alkaline lands, and water bodies. These lands have relatively distinct spectral and texture features. The spectral features along the beach show characteristics of absorption in the green band and reflection in the red band. This feature is less affected by the acquisition year, season, and sensor type. Saline-alkali land due to the influence of some saline-alkaline-tolerant plants such as alkali tent, Tamarix and other vegetation, the spectral characteristics have a certain seasonal changes, winter and spring NDVI index is less than the summer and autumn vegetation index. The spectral characteristics of a water body generally decrease rapidly with increasing wavelength, and the reflectance in the red band increases with increasing sediment concentration. In conclusion, according to the spectral characteristics and image texture features of the ecological land in the Yellow River Delta, the accuracy of image interpretation of such ecological land can be improved.

Land Cover and Seasonality Effects on Biomass Burning Emissions and Air Quality Impacts Observed from Satellites

NASA Astrophysics Data System (ADS)

Zoogman, P.; Hoffman, A.; Gonzalez Abad, G.; Miller, C. E.; Nowlan, C. R.; Huang, G.; Liu, X.; Chance, K.

2016-12-01

Trace gas emissions from biomass burning can vary greatly both regionally and from event to event, but our current scientific understanding is unable to fully explain this variability. The large uncertainty in ozone formation resulting from fire emissions has posed a great challenge for assessing fire impacts on air quality and atmospheric composition. Satellite observations from OMI offer a powerful tool to observe biomass burning events by providing observations globally over a range of environmental conditions that effect emissions of NOx, formaldehyde, and glyoxal. We have investigated the seasonal relationship of biomass burning enhancements of these trace gases derived from OMI observations over tropical South America, Africa, and Indonesia. Land cover type (also derived from satellite observations) has a significant impact on formaldehyde and glyoxal enhancements from fire activity. We have found that the chemical ratio between formaldehyde and glyoxal is dependent on the burned land type and will present our current hypotheses for the spatial variation of this ratio in the tropics. Furthermore, in individual case studies we will investigate how these chemical ratios can inform our knowledge of the secondary formation of ozone, particularly during exceptional pollution events.

Multisource Imaging of Seasonal Dynamics in Land Surface Phenology Using Harmonized Landsat and Sentinel-2 Data

NASA Astrophysics Data System (ADS)

Melaas, E. K.; Graesser, J.; Friedl, M. A.

2017-12-01

Land surface phenology, including the timing of phenophase transitions and the entire seasonal cycle of surface reflectance and vegetation indices, is important for a myriad of applications including monitoring the response of terrestrial ecosystems to climate variability and extreme events, and land cover mapping. While methods to monitor and map phenology from coarse spatial resolution instruments such as MODIS are now relatively mature, the spatial resolution of these instruments is inadequate where vegetation properties, land use, and land cover vary at spatial scales of tens of meters. To address this need, algorithms to map phenology at moderate spatial resolution (30 m) using data from Landsat have recently been developed. However, the 16-day repeat cycle of Landsat presents significant challenges in regions where changes are rapid or where cloud cover reduces the frequency of clear-sky views. The European Space Agency's Sentinel-2 satellites, which are designed to provide moderate spatial resolution data at 5-day revisit frequency near the equator and 3 day revisit frequency in the mid-latitudes, will alleviate this constraint in many parts of the world. Here, we use harmonized time series of data from Sentinel-2A and Landsat OLI (HLS) to quantify the timing of land surface phenology metrics across a sample of deciduous forest and grassland-dominated sites, and then compare these estimates with co-located in situ observations. The resulting phenology maps demonstrate the improved information related to landscape-scale features that can be estimated from HLS data relative to comparable metrics from coarse spatial resolution instruments. For example, our results based on HLS data reveal spatial patterns in phenological metrics related to topographic and land cover controls that are not resolved in MODIS data, and show good agreement with transition dates observed from in situ measurements. Our results also show systematic bias toward earlier timing of spring

A Comparison Between SST and AOT Derived from AVHRR and MODIS Data in the Frame of the CREPAD Program

NASA Astrophysics Data System (ADS)

Robles-Gonzalez, Cristina; Fernandez-Renau, Alix; Lopez Gordillo, Noelia; Sevilla, Angel Garcia; Suarez, Juana Santana

2010-12-01

Since 1997, the INTA-CREPAD (Centre for REception, Processing, Archiving and Dissemination of Earth Observation Data) program distributes freely some of the most demanded low-resolution remote sensing products: SST, Ocean Chl-a, NDVI, AOD... The data input for such products are captured at the Canary Space Station (Centro Espacial de Canarias, CEC). The data sensors received at the station and used in the CREPAD program are AVHRR, SEAWIFS and MODIS. In this study SST and AOD retrieved by CREPAD algorithms from AVHRR and the SEADAS derived SST and AOD from MODIS have compared. SST values agree very well within 0.1±0.5oC and the coefficient of correlation of the images is 0.9. AOD validation gives good results taking into account the differences in the algorithms used. Mean AOD difference at 0.630 μm is 0.01±0.05 and the correlation coefficient is 0.6.

Faunal diversity during rainy season in reclaimed sodic land of Uttar Pradesh, India.

PubMed

Singh, S K; Srivastava, S P; Tandon, Pankaj; Azad, B S

2009-07-01

Faunal diversity is an indicator of soil amelioration. Estimating the population size or density of an animal species in an area is fundamental to understand its status and demography and to plan for its management and conservation. Considering this, faunal diversity in reclamed sodic land was monitored during rainy season 2000-01 at different locations of district viz., Aligarh, Etah, Fatehpur, Mainpuri and Raebareli in Uttar Pradesh. The Shannon-Weiner species diversity index (H) of different fauna complex of each location was compared with zero years (1995-1996) indexes (before reclamation). Insects diversity index, in reclaimed sodic soil, varied from 3.8178 (Fatehpur: Bariyampur) to 4.623 (Fatehpur: Katoghan), which was 3.028 in zero year at Katoghan in Fatehpur 'H' index of other-arthropods ranged widely from 0.9743 (Etah: Bawali) to 2.0674 (Mainpuri: Pundari). The species diversity index of molluscs registered as high as 1.8637 at Ladhauwa site in Aligarh, which exhibited identical with Saripur site of Raebareli. 'H' index of mammal resulted with the highest (2.19) at Pundari in district Mainpuri. The avifauna and amphibian's indices were recovered maximal at Saripur site of Raebareli and Bariyampur site of Fatehpur respectively. Our result revealed that various fauna enriched with soil reclamation, which is good indicator of restoration of land, primarily due to soil-arthropods and earthworms and its eventual improvement along with succeeding rice-wheat cropping system widespread over there. It clearly shows that soil fauna strongly affects the composition of natural vegetation and we suggest that this knowledge might improve the restoration and conservation of biodiversity.

Seasonal-to-interannual variation in biomass burning over the contiguous United States

NASA Astrophysics Data System (ADS)

Kim, K. M.; Lau, W. K. M.; Ichoku, I.; Pereira, G.; Darmenov, A.; da Silva, A. M., Jr.; Ellison, L.

2017-12-01

The intensity and frequency of wildfires are strongly affected by climatic factors, such as droughts and heat waves, which are governed by weather and climate dynamics. . Climatic impacts on wildfire and biomass burning can be complex involving not only natural variability, but also human activities. In this study, we examine the seasonality of occurrences and intensity of fires and climatic impact as a function of underlying biomes over the CONUS, using fire pixel data from MODIS instruments on-board Terra and Aqua. Results show that there are three distinct fire seasons, i.e., summer (June to August), spring (March-April), and Fall (September-October). In the evergreen needle leaf region where most fires occur, the fire season peaks in mid boreal summer. In this region, fires tend to start early (June) in southern US, and late (August) in northern US. Double peaks are distinctive features in grass land and crop land. Double peaks in crop land (spring and fall) appear to be associated with agricultural practices. However, the two peaks in grass land (spring and summer) are due to natural wildfires, associated with changes in seasonal weather pattern. To better understand the potential climatic impact on fire, we examine relationships between fire weather index (FWI) and fire pixel counts. Fire pixel count has a strong correlation with FWI in evergreen needle leaf forest, deciduous broad leaf forest, and open shrub land. However, no significant linear relations are found in crop land, grass land, and mixed forest. The implications of these findings, and possible impacts of atmospheric teleconnecon on the fire season in the CONUS will also be discussed.

Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2): atmosphere-land-ocean-sea ice coupled prediction system for operational seasonal forecasting

NASA Astrophysics Data System (ADS)

Takaya, Yuhei; Hirahara, Shoji; Yasuda, Tamaki; Matsueda, Satoko; Toyoda, Takahiro; Fujii, Yosuke; Sugimoto, Hiroyuki; Matsukawa, Chihiro; Ishikawa, Ichiro; Mori, Hirotoshi; Nagasawa, Ryoji; Kubo, Yutaro; Adachi, Noriyuki; Yamanaka, Goro; Kuragano, Tsurane; Shimpo, Akihiko; Maeda, Shuhei; Ose, Tomoaki

2018-02-01

This paper describes the Japan Meteorological Agency/Meteorological Research Institute-Coupled Prediction System version 2 (JMA/MRI-CPS2), which was put into operation in June 2015 for the purpose of performing seasonal predictions. JMA/MRI-CPS2 has various upgrades from its predecessor, JMA/MRI-CPS1, including improved resolution and physics in its atmospheric and oceanic components, introduction of an interactive sea-ice model and realistic initialization of its land component. Verification of extensive re-forecasts covering a 30-year period (1981-2010) demonstrates that JMA/MRI-CPS2 possesses improved seasonal predictive skills for both atmospheric and oceanic interannual variability as well as key coupled variability such as the El Niño-Southern Oscillation (ENSO). For ENSO prediction, the new system better represents the forecast uncertainty and transition/duration of ENSO phases. Our analysis suggests that the enhanced predictive skills are attributable to incremental improvements resulting from all of the changes, as is apparent in the beneficial effects of sea-ice coupling and land initialization on 2-m temperature predictions. JMA/MRI-CPS2 is capable of reasonably representing the seasonal cycle and secular trends of sea ice. The sea-ice coupling remarkably enhances the predictive capability for the Arctic 2-m temperature, indicating the importance of this factor, particularly for seasonal predictions in the Arctic region.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Shukla, Shraddhanand; Arsenault, Kristi R.; Getirana, Augusto; Kumar, Sujay V.; Roningen, Jeanne; Zaitchik, Ben; McNally, Amy; Koster, Randal D.; Peters-Lidard, Christa

2017-04-01

Drought and water scarcity are among the important issues facing several regions within Africa and the Middle East. A seamless and effective monitoring and early warning system is needed by regional/national stakeholders. Such system should support a proactive drought management approach and mitigate the socio-economic losses up to the extent possible. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of the LIS models used for drought and water availability monitoring in the region. The second part will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the monitoring and forecasting products through NASA's web-services. The water deficit forecasting system thus far incorporates NOAA's Noah land surface model (LSM), version 3.3, the Variable Infiltration Capacity (VIC) model, version 4.12, NASA GMAO's Catchment LSM, and the Noah Multi-Physics (MP) LSM (the latter two incorporate prognostic water table schemes). In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. The LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. The LIS software framework integrates these forcing datasets and drives the four LSMs and HyMAP. The Land Verification Toolkit (LVT) is used for the evaluation of the

Local to Global Scale Time Series Analysis of US Dryland Degradation Using Landsat, AVHRR, and MODIS

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Ramsey, R. D.; West, N. E.; Kulawardhana, W.; Reeves, M. C.; Mitchell, J. E.; Van Niel, T. G.

2011-12-01

Drylands cover 41% of the terrestrial land surface and annually generate $1 trillion in ecosystem goods and services for 38% of the global population, yet estimates of the global extent of Dryland degradation is uncertain with a range of 10 - 80%. It is currently understood that Drylands exhibit topological complexity including self-organization of parameters of different levels-of-organization, e.g., ecosystem and landscape parameters such as soil and vegetation pattern and structure, that gradually or discontinuously shift to multiple basins of attraction in response to herbivory, fire, and climatic drivers at multiple spatial and temporal scales. Our research has shown that at large geographic scales, contemporaneous time series of 10 to 20 years for response and driving variables across two or more spatial scales is required to replicate and differentiate between the impact of climate and land use activities such as commercial grazing. For example, the Pacific Decadal Oscillation (PDO) is a major driver of Dryland net primary productivity (NPP), biodiversity, and ecological resilience with a 10-year return interval, thus 20 years of data are required to replicate its impact. Degradation is defined here as a change in physiognomic composition contrary to management goals, a persistent reduction in vegetation response, e.g., NPP, accelerated soil erosion, a decline in soil quality, and changes in landscape configuration and structure that lead to a loss of ecosystem function. Freely available Landsat, Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradimeter (MODIS) archives of satellite imagery exist that provide local to global spatial coverage and time series between 1972 to the present from which proxies of land degradation can be derived. This paper presents time series assessments between 1972 and 2011 of US Dryland degradation including early detection of dynamic regime shifts in the Mojave and landscape pattern and

Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements

PubMed Central

Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

2008-01-01

This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG). We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand large-scale vegetation growth dynamics above the tree line in the European Alps. PMID:27879852

Alpine Grassland Phenology as Seen in AVHRR, VEGETATION, and MODIS NDVI Time Series - a Comparison with In Situ Measurements.

PubMed

Fontana, Fabio; Rixen, Christian; Jonas, Tobias; Aberegg, Gabriel; Wunderle, Stefan

2008-04-23

This study evaluates the ability to track grassland growth phenology in the Swiss Alps with NOAA-16 Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) time series. Three growth parameters from 15 alpine and subalpine grassland sites were investigated between 2001 and 2005: Melt-Out (MO), Start Of Growth (SOG), and End Of Growth (EOG).We tried to estimate these phenological dates from yearly NDVI time series by identifying dates, where certain fractions (thresholds) of the maximum annual NDVI amplitude were crossed for the first time. For this purpose, the NDVI time series were smoothed using two commonly used approaches (Fourier adjustment or alternatively Savitzky-Golay filtering). Moreover, AVHRR NDVI time series were compared against data from the newer generation sensors SPOT VEGETATION and TERRA MODIS. All remote sensing NDVI time series were highly correlated with single point ground measurements and therefore accurately represented growth dynamics of alpine grassland. The newer generation sensors VGT and MODIS performed better than AVHRR, however, differences were minor. Thresholds for the determination of MO, SOG, and EOG were similar across sensors and smoothing methods, which demonstrated the robustness of the results. For our purpose, the Fourier adjustment algorithm created better NDVI time series than the Savitzky-Golay filter, since latter appeared to be more sensitive to noisy NDVI time series. Findings show that the application of various thresholds to NDVI time series allows the observation of the temporal progression of vegetation growth at the selected sites with high consistency. Hence, we believe that our study helps to better understand largescale vegetation growth dynamics above the tree line in the European Alps.

Polar cloud and surface classification using AVHRR imagery - An intercomparison of methods

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Goroch, A. K.; Rabindra, P.; Rangaraj, N.; Navar, M. S.

1992-01-01

Six Advanced Very High-Resolution Radiometer local area coverage (AVHRR LAC) arctic scenes are classified into ten classes. Three different classifiers are examined: (1) the traditional stepwise discriminant analysis (SDA) method; (2) the feed-forward back-propagation (FFBP) neural network; and (3) the probabilistic neural network (PNN). More than 200 spectral and textural measures are computed. These are reduced to 20 features using sequential forward selection. Theoretical accuracy of the classifiers is determined using the bootstrap approach. Overall accuracy is 85.6 percent, 87.6 percent, and 87.0 percent for the SDA, FFBP, and PNN classifiers, respectively, with standard deviations of approximately 1 percent.

Some practical aspects of lossless and nearly-lossless compression of AVHRR imagery

NASA Technical Reports Server (NTRS)

Hogan, David B.; Miller, Chris X.; Christensen, Than Lee; Moorti, Raj

1994-01-01

Compression of Advanced Very high Resolution Radiometers (AVHRR) imagery operating in a lossless or nearly-lossless mode is evaluated. Several practical issues are analyzed including: variability of compression over time and among channels, rate-smoothing buffer size, multi-spectral preprocessing of data, day/night handling, and impact on key operational data applications. This analysis is based on a DPCM algorithm employing the Universal Noiseless Coder, which is a candidate for inclusion in many future remote sensing systems. It is shown that compression rates of about 2:1 (daytime) can be achieved with modest buffer sizes (less than or equal to 2.5 Mbytes) and a relatively simple multi-spectral preprocessing step.

Spaceborne estimated long-term trends (1980s - 2013) of albedo and melting season length over the Greenland ice sheet and linkages to climate drivers

NASA Astrophysics Data System (ADS)

Tedesco, M.; Stroeve, J. C.

2014-12-01

The length of the melting season and surface albedo modulate the amount of meltwater produced over the Greenland ice sheet. The two quantities are intimately connected through a suite of non-linear processes: for example, early melting can reduce the surface albedo (through constructive grain size metamorphism), hence affecting the surface energy balance and further increasing melting. Over the past years, several studies have highlighted increased melting concurring, with a decrease of mean surface albedo over Greenland. However, few studies have examined the duration of the melting season, its implication for surface processes and linkages to climate drivers. Moreover, the majority (if not all) of the studies assessing albedo trends from spaceborne data over Greenland have focused on the last decade or so (2000 - 2013) because they use data collected over the same period by the Moderate Resolution Imaging Spectroradiometer (MODIS). Here, we evaluate and synthesize long-term trends in the length of the melting season (1979 - 2013) derived from spaceborne microwave observations together with surface albedo trends for the period 1982 - 2013 using data from the Advanced Very High Resolution Radiometer (AVHRR). To our knowledge, this is the first time that trends in Greenland albedo and melt season length are discussed for the periods considered in this study. Our results point to a lengthening of the melting season as a consequence of earlier melt onset and later refreeze and to a decrease of mean albedo (1982 - 2013) over the Greenland ice sheet, with trends being spatially variable. To account for this spatial variability, the results of an analysis at regional scales over 12 different regions (defined by elevation and drainage systems) are also reported. The robustness of the results is evaluated by means of a comparative analysis of the results obtained from both AVHRR and MODIS when overlapping data are available (2000 - 2013). Lastly, because large

Utilizing remote sensing data for modeling water and heat regimes of the Black Earth Region territory of the European Russia

NASA Astrophysics Data System (ADS)

Muzylev, Eugene; Startseva, Zoya; Uspensky, Alexander; Volkova, Elena; Uspensky, Sergey

2014-05-01

At present physical-mathematical modeling processes of water and heat exchange between vegetation covered land surfaces and atmosphere is the most appropriate method to describe peculiarities of water and heat regime formation for large territories. The developed model of such processes (Land Surface Model, LSM) is intended for calculation evaporation, transpiration by vegetation, soil water content and other water and heat regime characteristics, as well as distributions of the soil temperature and humidity in depth utilizing remote sensing data from satellites on land surface and meteorological conditions. The model parameters and input variables are the soil and vegetation characteristics and the meteorological characteristics, correspondingly. Their values have been determined from ground-based observations or satellite-based measurements by radiometers AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/Meteosat-9, -10. The case study has been carried out for the part of the agricultural Central Black Earth region with coordinates 49.5 deg. - 54 deg. N, 31 deg. - 43 deg. E and a total area of 227,300 km2 located in the steppe-forest zone of the European Russia for years 2009-2012 vegetation seasons. From AVHRR data there have been derived the estimates of three types of land surface temperature (LST): land surface skin temperature Tsg, air-foliage temperature Ta and efficient radiation temperature Ts.eff, emissivity E, normalized vegetation index NDVI, vegetation cover fraction B, leaf area index LAI, cloudiness and precipitation. From MODIS data the estimates of LST Tls, E, NDVI and LAI have been obtained. The SEVIRI data have been used to build the estimates of Tls, Ta, E, LAI and precipitation. Previously developed method and technology of above AVHRR-derived estimates have been improved and adapted to the study area. To check the reliability of the Ts.eff and Ta estimations for named seasons the error statistics of their definitions has been analyzed through

Seasonally asymmetric enhancement of northern vegetation productivity

NASA Astrophysics Data System (ADS)

Park, T.; Myneni, R.

2017-12-01

Multiple evidences of widespread greening and increasing terrestrial carbon uptake have been documented. In particular, enhanced gross productivity of northern vegetation has been a critical role leading to observed carbon uptake trend. However, seasonal photosynthetic activity and its contribution to observed annual carbon uptake trend and interannual variability are not well understood. Here, we introduce a multiple-source of datasets including ground, atmospheric and satellite observations, and multiple process-based global vegetation models to understand how seasonal variation of land surface vegetation controls a large-scale carbon exchange. Our analysis clearly shows a seasonally asymmetric enhancement of northern vegetation productivity in growing season during last decades. Particularly, increasing gross productivity in late spring and early summer is obvious and dominant driver explaining observed trend and variability. We observe more asymmetric productivity enhancement in warmer region and this spatially varying asymmetricity in northern vegetation are likely explained by canopy development rate, thermal and light availability. These results imply that continued warming may facilitate amplifying asymmetric vegetation activity and cause these trends to become more pervasive, in turn warming induced regime shift in northern land.

City landscape changes effects on land surface temperature in Bucharest metropolitan area

NASA Astrophysics Data System (ADS)

Savastru, Dan M.; Zoran, Maria A.; Savastru, Roxana S.; Dida, Adrian I.

2017-10-01

This study investigated the influences of city land cover changes and extreme climate events on land surface temperature in relationship with several biophysical variables in Bucharest metropolitan area of Romania through satellite and in-situ monitoring data. Remote sensing data from IKONOS, Landsat TM/ETM+ and time series MODIS Terra/Aqua and NOAA AVHRR sensors have been used to assess urban land cover- temperature interactions over 2000 - 2016 period. Time series Thermal InfraRed (TIR) satellite remote sensing data in synergy with meteorological data (air temperatureAT, precipitations, wind, solar radiation, etc.) were applied mainly for analyzing land surface temperature (LST) pattern and its relationship with surface landscape characteristics, assessing urban heat island (UHI), and relating urban land cover temperatures (LST). The land surface temperature, a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Results show that in the metropolitan area ratio of impervious surface in Bucharest increased significantly during investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, LST and AT possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at metropolitan scale respectively. The NDVI was significantly correlated with precipitation. The spatial average air temperatures in urban test areas rise with the expansion of the urban size.

Effect of Climate Change on Vegetation Phenology of Different Land Cover Types on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Cheng, M.; Jin, J.

2017-12-01

Vegetation phenology is one of the most sensitive bio-indicators of climate change, and it has received increasing interests in the context of global warming. As one of the most sensitive areas to global change, the Tibetan Plateau is a unique region to study the trends in vegetation phenology in response to climate change because of its unique vegetation composition, climate features and low-level human disturbance. Although some studies have aroused wide controversies about the actual plant phenology patterns in the Tibetan Plateau, yet the reasons remain unclear. In particular, the phenology characteristics of sparse herbaceous or sparse shrub and evergreen forest that are mostly located in the northwest and southeast of the Tibetan Plateau remain less studied. In this study, the spatio-temporal patterns of the start (SOS), end (EOS) and length (LOS) of the vegetation growing season for six vegetation types in the Tibetan Plateau, including evergreen broadleaf forests, evergreen coniferous forests, evergreen shrub, meadow, steppe and sparse herbaceous or sparse shrub, were quantified from 1982 to 2014 using NOAA/AVHRR NDVI data set at a spatial resolution of 0.05°×0.05° and 7-day intervals using NDVI relative change rate threshold and sixth order polynomial fit models. Assisted with the monthly precipitation and temperature data, the relative effects of changing climates on the variability of phenology were also examined. Diverse phenological changes were observed for different land cover types, with an advancing start of growing season (SOS), delaying end of growing season (EOS) and increasing length of growing season (LOS) in the eastern Tibetan Plateau where meadow was the dominant vegetation type, but with the opposite changes in the steppe and sparse herbaceous or sparse shrub regions which are mostly located in the northwestern and western edges of the Tibetan Plateau. Correlation analysis indicated that sufficient preseason precipitation may delay the

Estimating Evapotranspiration Demands of Different Land Cover Using Diurnal Signals in Dry Season Stream Discharge

NASA Astrophysics Data System (ADS)

Bhalla, R. S.; K, K.; Srinivas, V.; Krishnaswamy, J.; Chappell, N. A.; Jones, T.

2015-12-01

We use a paired catchment approach to compare the dry season flows between natural grasslands and introduced plantations of black wattle (Acacia mearnsii) in the Nilgiri South range forest which lies in the southern parts of the Western Ghat mountain range in Sothern India, a global biodiversity hot-spot. Discharges were measured using a portable flume and a weir fitted with capacitance probes logging water levels every five minutes in two adjacent catchments. Sensor artefacts in the data were filtered out before analysis. Diurnal variations in dry season flows from March 1st to April 15th, 2014 were used to estimate the daily ET based on Boronina et al. 2005 (Hyd. Proc. 19, 20, pp. 4055-4068.) using the equation 1. : E T daily = ∑ i=1 24 ( Q max - Q i ) Δ t , where E T daily is the daily loss of water from the catchment through ET, Q max is the daily maximum flow rate in the river, Q i is the average flow rate for every hour of the day and Δ t is one hour. Our results show that land use conversion from grasslands to wattle has increased ET by 40.97mm which is to the order of 60% during the period of the study (table 1). This has immediate relevance for dry season flows in the region. Nilgiris provide 40% of the total hydro-power generation for the state of Tamil Nadu and these streams sustain biodiversity and are tributaries of the Cauvery river, the largest the state. They also highlight the potential consequences of programmes such as the National Mission for Greening India which explicitly targets conversions of 10m ha of degraded forests, scrub and grasslands to tree cover and forest. Grassland Wattle Difference 1st Qu. 1.14 1.36 -1.33 Median 1.94 2.04 0.28 Mean 2.06 2.97 0.91 3rd Qu. 2.66 3.51 2.43 Sum 92.63 133.60 40.97 Table 1: Summary statistics for daily dry season ET for catchment under grassland, wattle and the daily differences between the two in mm per day.

Mapping Landscape Phenology Preference of Yellow-billed Cuckoo with AVHRR data

NASA Astrophysics Data System (ADS)

Wallace, C.; Villarreal, M. L.; Van Riper, C., III

2011-12-01

The yellow-billed cuckoo (Coccycus americanus occidentalis) is a neo-tropical migrant bird that travels north from South America into the southwestern United States during the summer to nest. In Arizona, favored riparian forest and woodland nesting habitat has declined in recent decades, due primarily to human activities and the prolonged drought conditions. As a result, western yellow-billed cuckoos have been petitioned for possible listing under the Endangered Species Act. In this study, we map yellow-billed cuckoo habitat in the state of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) satellite Normalized Difference Vegetation Index (NDVI) composite data using Fourier harmonic analysis. Applying Fourier analysis to the waveform composed of the 26 annual composite NDVI values produces phenometrics related to the overall vegetation amount, variability and timing. Field data on Cuckoo presence were obtained from 1998 surveys conducted by Northern Arizona University (NAU), the Arizona Game and Fish Department (AGFD) and the U.S. Geological Survey (USGS). To focus the research within probable landscapes, an AGFD vegetation map (derived from the Arizona GAP program) was used to extract polygons of riparian vegetation and cottonwood-willow riparian vegetation. To create the models, we coupled the satellite phenometrics with field data of cuckoo presence or absence and with points sampling the entirety of mapped riparian and cottonwood-willow vegetation types. Statistical tests reveal that locations with cuckoos present are landscapes with greenness that is significantly more variable and that peaks significantly later than locations in average riparian vegetation, average cottonwood-willow vegetation, or with cuckoos absent. Interestingly, the mean peak greenness date of July 3 for survey locations with cuckoos present coincides with the

Definition and testing of the hydrologic component of the pilot land data system

NASA Technical Reports Server (NTRS)

Ragan, Robert M.; Sircar, Jayanta K.

1987-01-01

The specific aim was to develop within the Pilot Land Data System (PLDS) software design environment, an easily implementable and user friendly geometric correction procedure to readily enable the georeferencing of imagery data from the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA series spacecraft. A software subsystem was developed within the guidelines set by the PLDS development environment utilizing NASA Goddard Space Flight Center (GSFC) Image Analysis Facility's (IAF's) Land Analysis Software (LAS) coding standards. The IAS current program development environment, the Transportable Applications Executive (TAE), operates under a VAX VMS operating system and was used as the user interface. A brief overview of the ICARUS algorithm that was implemented in the set of functions developed, is provided. The functional specifications decription is provided, and a list of the individual programs and directory names containing the source and executables installed in the IAF system are listed. A user guide is provided for the LAS system documentation format for the three functions developed.

An approach for using AVHRR data to monitor U.S. great plains grasslands

USGS Publications Warehouse

Reed, B.C.; Loveland, Thomas R.; Tieszen, L.L.

1996-01-01

Environmental monitoring requires regular observations regarding the status of the landscape- The concept behind most monitoring efforts using satellite data involve deriving normalized difference vegetation index (NDVI) values or accumulating the NDVI over a specified time period. These efforts attempt to estimate the continuous growth of green biomass by using continuous additions of NDVI as a surrogate measure. To build upon this concept, this study proposes three refinements; 1) use an objective definition of the current growing season to adjust the time window during which the NDVI is accumulated, 2) accumulate only the NDVI values which are affected by green vegetation, and 3) base monitoring units upon land cover type. These refinements improve the sensitivity of detecting interannual vegetation variability, reduce the need for extensive and detailed knowledge of ground conditions and crop calendars, provide a framework in which several types of monitoring can take place over diverse land cover types, and provide an objective time frame during which monitoring takes place.

Thermal signatures of urban land cover types: High-resolution thermal infrared remote sensing of urban heat island in Huntsville, AL

NASA Technical Reports Server (NTRS)

Lo, Chor Pang

1996-01-01

The main objective of this research is to apply airborne high-resolution thermal infrared imagery for urban heat island studies, using Huntsville, AL, a medium-sized American city, as the study area. The occurrence of urban heat islands represents human-induced urban/rural contrast, which is caused by deforestation and the replacement of the land surface by non-evaporating and non-porous materials such as asphalt and concrete. The result is reduced evapotranspiration and more rapid runoff of rain water. The urban landscape forms a canopy acting as a transitional zone between the atmosphere and the land surface. The composition and structure of this canopy have a significant impact on the thermal behavior of the urban environment. Research on the trends of surface temperature at rapidly growing urban sites in the United States during the last 30 to 50 years suggests that significant urban heat island effects have caused the temperatures at these sites to rise by 1 to 2 C. Urban heat islands have caused changes in urban precipitation and temperature that are at least similar to, if not greater than, those predicted to develop over the next 100 years by global change models. Satellite remote sensing, particularly NOAA AVHRR thermal data, has been used in the study of urban heat islands. Because of the low spatial resolution (1.1 km at nadir) of the AVHRR data, these studies can only examine and map the phenomenon at the macro-level. The present research provides the rare opportunity to utilize 5-meter thermal infrared data acquired from an airplane to characterize more accurately the thermal responses of different land cover types in the urban landscape as input to urban heat island studies.

Climate Sensitivity Studies of the Greenland Ice Sheet Using Satellite AVHRR, SMMR, SSM/I and in Situ Data

NASA Technical Reports Server (NTRS)

Steffen, K.; Abdalati, W.; Stroeve, J.

1993-01-01

The feasibility of using satellite data for climate research over the Greenland ice sheet is discussed. In particular, we demonstrate the usefulness of Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) and Global Area Coverage (GAC) data for narrow-band albedo retrieval. Our study supports the use of lower resolution AVHRR (GAC) data for process studies over most of the Greenland ice sheet. Based on LAC data time series analysis, we can resolve relative albedo changes on the order of 2-5%. In addition, we examine Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave data for snow typing and other signals of climatological significance. Based on relationships between in situ measurements and horizontally polarized 19 and 37 GHz observations, wet snow regions are identified. The wet snow regions increase in aerial percentage from 9% of the total ice surface in June to a maximum of 26% in August 1990. Furthermore, the relationship between brightness temperatures and accumulation rates in the northeastern part of Greenland is described. We found a consistent increase in accumulation rate for the northeastern part of the ice sheet from 1981 to 1986.

Clouds as calibration targets for AVHRR reflected-solar channels - Results from a two-year study at NOAA/NESDIS

NASA Technical Reports Server (NTRS)

Abel, Peter

1991-01-01

NOAA-11 Advanced Very High Resolution Radiometer (AVHRR) and associated ground-based data have been collected at NOAA/NESDIS, on a daily basis and for 600 days, using five stations within the continental United States in the NOAA solar radiation (SOLRAD) monitoring network. The data have been filtered to include only uniformly overcast conditions and analyzed along the lines described by Paris and Justus (1988). Results from this first long-term pilot operational application of the method are presented. The method is potentially useful for establishing yearly-averaged trends in the radiometric gain of AVHRR Channels. The relatively small data base examined here suggests a precision in the 600 day mean gain of 5 percent or worse, with a significant part of this uncertainty being driven by poor knowlege of the bidirectional reflectance properties of clouds. The results suggest that the method in its present formulation has insufficient precision to be used as a primary method for the measurement of in-orbit gains of reflected-solar radiometers aboard polar orbiting satellites. Intrinsic limitations to the precision and time resolution of the method are discussed, and suggestions are offered for improving the precision of future results.

Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s

USGS Publications Warehouse

Stow, D.; Daeschner, Scott; Hope, A.; Douglas, David C.; Petersen, A.; Myneni, Ranga B.; Zhou, L.; Oechel, W.

2003-01-01

The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.

Local people's knowledge with regard to land use activities in southwest Madagascar - Conceptual insights for sustainable land management.

PubMed

Fritz-Vietta, Nadine V M; Tahirindraza, H Stone; Stoll-Kleemann, Susanne

2017-09-01

Environmental conditions in the Mahafaly Plateau region in southwest Madagascar are harsh, with a long dry season and a short rainy season. The local people's land use capabilities and skills are adapted to these conditions. Nevertheless, they are currently confronted by drastic climatic changes, including longer dry seasons, which have resulted in food and water scarcities. It is therefore essential to ensure sustainable land management in the region. At present, the main land use activities are agriculture, livestock farming, natural resource collection including timber and non-timber forest products, and the practice of local customs. Land use activities have always resulted in land conversion, yet over time this ecological transformation also leads to the accumulation of knowledge. The aim of the present article is therefore twofold. First, it aims to examine local people's knowledge with regard to land use activities and the transmission of this knowledge from one generation to the next; second, it considers the extent to which local people's knowledge may contribute to the development of sustainable land management. Our research is based on more than 80 qualitative interviews with local inhabitants of the Mahafaly Plateau region. Our analysis of local people's knowledge identifies four categories: ecological knowledge, knowledge related to natural resource usage, knowledge of names, and the interconnection between knowledge and belief. Furthermore, these knowledge categories provide conceptual insights for sustainable land management. Along with the long-term persistence of natural resources and their functions and the satisfaction of basic needs through resource usage, both the recognition of mental images as a regulating mechanism and the maintenance of the relation between the natural and the supernatural world have a role to play in sustainable land management in the study area. Local knowledge transmission processes serve to foster ongoing learning and

Runoff changes have a land cover specific effect on the seasonal fluxes of terminal electron acceptors in the boreal catchments.

PubMed

Mattsson, Tuija; Lehtoranta, Jouni; Ekholm, Petri; Palviainen, Marjo; Kortelainen, Pirkko

2017-12-01

Climate change influences the volume and seasonal distribution of runoff in the northern regions. Here, we study how the seasonal variation in the runoff affects the concentrations and export of terminal electron acceptors (i.e. TEAs: NO 3 , Mn, Fe and SO 4 ) in different boreal land-cover classes. Also, we make a prediction how the anticipated climate change induced increase in runoff will alter the export of TEAs in boreal catchments. Our results show that there is a strong positive relationship between runoff and the concentration of NO 3 -N, Mn and Fe in agricultural catchments. In peaty catchments, the relationship is poorer and the concentrations of TEAs tend to decrease with increasing runoff. In forested catchments, the correlation between runoff and TEA concentrations was weak. In most catchments, the concentrations of SO 4 decrease with an increase in runoff regardless of the land cover or season. The wet years export much higher amounts of TEAs than the dry years. In southern agricultural catchments, the wet years increased the TEA export for both spring (January-May) and autumn (September-December) periods, while in the peaty and forested catchments in eastern and northern Finland the export only increased in the autumn. Our predictions for the year 2099 indicate that the export of TEAs will increase especially from agricultural but also from forested catchments. Additionally, the predictions show an increase in the export of Fe and SO 4 for all the catchments for the autumn. Thus, the climate induced change in the runoff regime is likely to alter the exported amount of TEAs and the timing of the export downstream. The changes in the amounts and timing in the export of TEAs have a potential to modify the mineralization pathways in the receiving water bodies, with feedbacks in the cycling of C, nutrients and metals in aquatic ecosystems. Copyright © 2017 Elsevier B.V. All rights reserved.

Land use mapping and modelling for the Phoenix Quadrangle

NASA Technical Reports Server (NTRS)

Place, J. L. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Changes in the land use in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a land use classification system proposed for use with ERTS images. Seasonal changes were studied on successive ERTS-1 images, particularly large scale color composite transparencies for August, October, February, and May, and this seasonal variation aided delineation of land use boundaries. Types of equipment used to aid interpretation included color additive viewer, a twenty-power magnifier, a density slicer, and a diazo copy machine. A Zoom Transfer Scope was used for scale and photogrammetric adjustments. Types of changes detected have been: (1) cropland or rangeland developed as new residential areas; (2) rangeland converted to new cropland or to new reservoirs; and (3) possibly new activity by the mining industries. A map of land use previously compiled from air photos was updated in this manner. ERTS-1 images complemented air photos: the photos gave detail on a one-shot basis; the ERTS-1 images provided currency and revealed seasonal variation in vegetation which aided interpretation of land use.

Interannual Variations and Trends in Global Land Surface Phenology Derived from Enhanced Vegetation Index During 1982-2010

NASA Technical Reports Server (NTRS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-01-01

Land swiace phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstmted to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This srudy detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examIned across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and OSL varied considerably during 1982-2010 across the globe. Generally, the interarmual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative OSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

Interannual variations and trends in global land surface phenology derived from enhanced vegetation index during 1982-2010

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Tan, Bin; Yu, Yunyue

2014-05-01

Land surface phenology is widely retrieved from satellite observations at regional and global scales, and its long-term record has been demonstrated to be a valuable tool for reconstructing past climate variations, monitoring the dynamics of terrestrial ecosystems in response to climate impacts, and predicting biological responses to future climate scenarios. This study detected global land surface phenology from the advanced very high resolution radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from 1982 to 2010. Based on daily enhanced vegetation index at a spatial resolution of 0.05 degrees, we simulated the seasonal vegetative trajectory for each individual pixel using piecewise logistic models, which was then used to detect the onset of greenness increase (OGI) and the length of vegetation growing season (GSL). Further, both overall interannual variations and pixel-based trends were examined across Koeppen's climate regions for the periods of 1982-1999 and 2000-2010, respectively. The results show that OGI and GSL varied considerably during 1982-2010 across the globe. Generally, the interannual variation could be more than a month in precipitation-controlled tropical and dry climates while it was mainly less than 15 days in temperature-controlled temperate, cold, and polar climates. OGI, overall, shifted early, and GSL was prolonged from 1982 to 2010 in most climate regions in North America and Asia while the consistently significant trends only occurred in cold climate and polar climate in North America. The overall trends in Europe were generally insignificant. Over South America, late OGI was consistent (particularly from 1982 to 1999) while either positive or negative GSL trends in a climate region were mostly reversed between the periods of 1982-1999 and 2000-2010. In the Northern Hemisphere of Africa, OGI trends were mostly insignificant, but prolonged GSL was evident over individual climate regions during the last 3

[Effects of land use structure on water quality in Xin'anjiang River].

PubMed

Cao, Fang-Fang; Li, Xue; Wang, Dong; Zhao, Yue; Wang, Yu-Qiu

2013-07-01

Take Xin'anjiang upstream watershed as a case study. Based on data of interpreting TM orthophoto images and water quality monitoring in May 2010, the land use map of Xin'anjiang River, which was categorized to cultivated land, forestland, grassland, water body, building site, was obtained. Using ArcGIS hydrological and spatial analysis function, Xin'anjiang River was divided into eight sub-watersheds, and its watershed land use structure was analyzed. The water quality parameters such as TN, TP, permanganate index, fecal coliform bacteria were monitored from Jan 2010 to Dec 2010. The relations between water quality and land use were analyzed. The results showed that TN and NH4(+) -N had a significant temporal variation: dry season > wet season > normal river flow period, but other parameters did not vary significantly. In the space, Yuliang and Pukou were the most serious pollution sites. Cultivated land, water body, building site had a positive impact on water quality parameters, while there were negative correlation between the forestland and grassland. Annually, cultivated land had the most significantly important effect on TN, NH4(+) -N and permanganate index, and grassland had the most significantly important effect on TP. Cultivated land had the most prominently important impact on water quality parameters in dry season and wet season. What's more, in the normal river flow, cultivated land, grassland and forestland had the most remarkably important influence on TN, TP and fecal coliform bacteria respectively.

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and

Seasonal persistence of faecal indicator organisms in soil following dairy slurry application to land by surface broadcasting and shallow injection.

PubMed

Hodgson, Christopher J; Oliver, David M; Fish, Robert D; Bulmer, Nicholas M; Heathwaite, A Louise; Winter, Michael; Chadwick, David R

2016-12-01

Dairy farming generates large volumes of liquid manure (slurry), which is ultimately recycled to agricultural land as a valuable source of plant nutrients. Different methods of slurry application to land exist; some spread the slurry to the sward surface whereas others deliver the slurry under the sward and into the soil, thus helping to reduce greenhouse gas (GHG) emissions from agriculture. The aim of this study was to investigate the impact of two slurry application methods (surface broadcast versus shallow injection) on the survival of faecal indicator organisms (FIOs) delivered via dairy slurry to replicated grassland plots across contrasting seasons. A significant increase in FIO persistence (measured by the half-life of E. coli and intestinal enterococci) was observed when slurry was applied to grassland via shallow injection, and FIO decay rates were significantly higher for FIOs applied to grassland in spring relative to summer and autumn. Significant differences in the behaviour of E. coli and intestinal enterococci over time were also observed, with E. coli half-lives influenced more strongly by season of application relative to the intestinal enterococci population. While shallow injection of slurry can reduce agricultural GHG emissions to air it can also prolong the persistence of FIOs in soil, potentially increasing the risk of their subsequent transfer to water. Awareness of (and evidence for) the potential for 'pollution-swapping' is critical in order to guard against unintended environmental impacts of agricultural management decisions. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Variation in the helminth community structure of Thrichomys pachyurus (Rodentia: Echimyidae) in two sub-regions of the Brazilian Pantanal: the effects of land use and seasonality.

PubMed

Simões, R; Gentile, R; Rademaker, V; D'Andrea, P; Herrera, H; Freitas, T; Lanfredi, R; Maldonado, A

2010-09-01

The Pantanal is a large ecosystem located in South America. This preserved area is seasonally flooded due to abundant rainfall during the summer and the subsequent overflow of the Paraguai River. In this paper, we examine the helminth community structure in the wild rodent Thrichomys pachyurus during the wet and dry seasons in two locations of the preserved and cattle ranching areas in the Southern Pantanal. We identified 12 species of helminth, and, although we did not find any differences in species richness between locations within the Pantanal, we found that richness was higher during the wet season. Helminth species were largely aggregated in both farm locations and during seasons. The most common helminth species were more abundant during the dry season than during the wet season, which may have been due to the increased habitat availability and rodent population increase. The intensity of the infection also followed the same pattern for most helminths. The trichostrongylids (Heligmostrongylus crucifer, H. almeidai and Pudica cercomysi) were dominant at both farm locations. The land use of each area was not correlated with helminth diversity. However, species composition of the helminth community of T. pachyurus differed between locations and may be correlated with environmental differences between the habitats. The seasonality of the Pantanal was highly correlated with helminth parasitism in T. pachyurus.

Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

NASA Astrophysics Data System (ADS)

Saramul, Suriyan; Ezer, Tal

2014-11-01

The study addresses two important issues associated with sea level along the coasts of Thailand: first, the fast sea level rise and its spatial variation, and second, the monsoonal-driven seasonal variations in sea level. Tide gauge data that are more extensive than in past studies were obtained from several different local and global sources, and relative sea level rise (RSLR) rates were obtained from two different methods, linear regressions and non-linear Empirical Mode Decomposition/Hilbert-Huang Transform (EMD/HHT) analysis. The results show extremely large spatial variations in RSLR, with rates varying from ~ 1 mm y-1 to ~ 20 mm y-1; the maximum RSLR is found in the upper Gulf of Thailand (GOT) near Bangkok, where local land subsidence due to groundwater extraction dominates the trend. Furthermore, there are indications that RSLR rates increased significantly in all locations after the 2004 Sumatra-Andaman Earthquake and the Indian Ocean tsunami that followed, so that recent RSLR rates seem to have less spatial differences than in the past, but with high rates of ~ 20-30 mm y-1 almost everywhere. The seasonal sea level cycle was found to be very different between stations in the GOT, which have minimum sea level in June-July, and stations in the Andaman Sea, which have minimum sea level in February. The seasonal sea-level variations in the GOT are driven mostly by large-scale wind-driven set-up/set-down processes associated with the seasonal monsoon and have amplitudes about ten times larger than either typical steric changes at those latitudes or astronomical annual tides.

Wildfire seasonality and land use: when do wildfires prefer to burn?

PubMed

Bajocco, Sofia; Pezzatti, Gianni Boris; Mazzoleni, Stefano; Ricotta, Carlo

2010-05-01

Because of the increasing anthropogenic fire activity, understanding the role of land-use in shaping wildfire regimes has become a major concern. In the last decade, an increasing number of studies have been carried out on the relationship between land-use and wildfire patterns, in order to identify land-use types where fire behaves selectively, showing a marked preference (or avoidance) in terms of fire incidence. By contrast, the temporal aspects of the relationship between landuse types and wildfire occurrence have received far less attention. The aim of this paper is, thus, to analyze the temporal patterns of fire occurrence in Sardinia (Italy) during the period 2000-2006 to identify land-use types where wildfires occur earlier or later than expected from a random null model. The study highlighted a close relationship between the timing of fire occurrence and land-cover that is primarily governed by two complementary processes: climatic factors that act indirectly on the timing of wildfires determining the spatial distribution of land-use types, and human population and human pressure that directly influence fire ignition. From a practical viewpoint, understanding the temporal trends of wildfires within the different land-use classes can be an effective decision-support tool for fire agencies in managing fire risk and for producing provisional models of fire behavior under changing climatic scenarios and evolving landscapes.

Land ECVs from QA4ECV using an optimal estimation framework

NASA Astrophysics Data System (ADS)

Muller, Jan-Peter; Kharbouche, Said; Lewis, Philip; Danne, Olaf; Blessing, Simon; Giering, Ralf; Gobron, Nadine; Lanconelli, Christian; Govaerts, Yves; Schulz, Joerg; Doutriaux-Boucher, Marie; Lattanzio, Alessio; Aoun, Youva

2017-04-01

In the ESA-DUE GlobAlbedo project (http://www.GlobAlbedo.org), a 15 year record of land surface albedo was generated from the European VEGETATION & MERIS sensors using optimal estimation. This was based on 3 broadbands (0.4-0.7, 0.7-3, 0.4-3µm) and fused data at level-2 after converting from spectral narrowband to these 3 broadbands with surface BRFs. A 10 year long record of land surface albedo climatology was generated from Collection 5 of the MODIS BRDF product for these same broadbands. This was employed as an a priori estimate for an optimal estimation based retrieval of land surface albedo when there were insufficient samples from the European sensors. This so-called MODIS prior was derived at 1km from the 500m MOD43A1,2 BRDF inputs every 8 days using the QA bits and the method described in the GlobAlbedo ATBD which is available from the website (http://www.globalbedo.org/docs/GlobAlbedo_Albedo_ATBD_V4.12.pdf). In the ESA-STSE WACMOS-ET project, FastOpt generated fapar & LAI based on this GlobAlbedo BRDF with associated per pixel uncertainty using the TIP framework. In the successor EU-FP7-QA4ECV* project, we have developed a 33 year record (1981-2014) of Earth surface spectral and broadband albedo (i.e. including the ocean and sea-ice) using optimal estimation for the land and where available, relevant sensors for "instantaneous" retrievals over the poles (Kharbouche & Muller, this conference). This requires the longest possible land surface spectral and broadband BRDF record that can only be supplied by a 16 year of MODIS Collection 6 BRDFs at 500m but produced on a daily basis. The CEMS Big Data computer at RAL was used to generate 7 spectral bands and 3 broadband BRDF with and without snow and snow_only. We will discuss the progress made since the start of the QA4ECV project on the production of a new fused land surface BRDF/albedo spectral and broadband CDR product based on four European sensors: MERIS, (A)ATSR(2), VEGETATION, PROBA-V and two US sensors

Seasonal homes and natural resources: patterns of use and impact in Michigan.

Treesearch

Daniel J. Stynes; JiaJia Zheng; Susan I. Stewart

1997-01-01

Describes patterns of seasonal home ownerships and use in northern lower Michigan, including recreational use of nearby public and private lands and potential use of the seasonal home as a retirement home. Estimates economic impacts associated with seasonal home related spending in the 33 counties of northern lower Michigan.

The Response of African Land Surface Phenology to Large Scale Climate Oscillations

NASA Technical Reports Server (NTRS)

Brown, Molly E.; de Beurs, Kirsten; Vrieling, Anton

2010-01-01

Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), and the Multivariate ENSO Index (MEI). We map the most significant positive and negative correlation for the four climate indices in Eastern, Western and Southern Africa between two phenological metrics and the climate indices. Our objective is to provide evidence of whether climate variability captured in the four indices has had a significant impact on the vegetative productivity of Africa during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by large scale variations in climate. The particular climate index and the timing showing highest correlation depended heavily on the region examined. In Western Africa the cumulative NDVI correlates with PDO in September-November. In Eastern Africa the start of the June-October season strongly correlates with PDO in March-May, while the PDO in December-February correlates with the start of the February-June season. The cumulative NDVI over this last season relates to the MEI of March-May. For Southern Africa, high correlations exist between SOS and NAO of September-November, and cumulative NDVI and MEI of March-May. The research shows that climate indices can be used to anticipate late start and variable vigor in the growing season of sensitive agricultural regions in Africa.

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Suarez, Max J.; Heiser, Mark

1999-01-01

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

50 CFR 648.322 - Skate allocation, possession, and landing provisions.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 50 Wildlife and Fisheries 8 2010-10-01 2010-10-01 false Skate allocation, possession, and landing... Management Measures for the NE Skate Complex Fisheries § 648.322 Skate allocation, possession, and landing... TAL not landed in Seasons 1 or 2 shall be allocated. (b) Skate wing possession and landing limits. A...

50 CFR 648.322 - Skate allocation, possession, and landing provisions.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 50 Wildlife and Fisheries 10 2011-10-01 2011-10-01 false Skate allocation, possession, and landing... Management Measures for the NE Skate Complex Fisheries § 648.322 Skate allocation, possession, and landing... TAL not landed in Seasons 1 or 2 shall be allocated. (b) Skate wing possession and landing limits. A...

The Impact of Soil Moisture Initialization On Seasonal Precipitation Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Suarez, M. J.; Tyahla, L.; Houser, Paul (Technical Monitor)

2002-01-01

Some studies suggest that the proper initialization of soil moisture in a forecasting model may contribute significantly to the accurate prediction of seasonal precipitation, especially over mid-latitude continents. In order for the initialization to have any impact at all, however, two conditions must be satisfied: (1) the initial soil moisture anomaly must be "remembered" into the forecasted season, and (2) the atmosphere must respond in a predictable way to the soil moisture anomaly. In our previous studies, we identified the key land surface and atmospheric properties needed to satisfy each condition. Here, we tie these studies together with an analysis of an ensemble of seasonal forecasts. Initial soil moisture conditions for the forecasts are established by forcing the land surface model with realistic precipitation prior to the start of the forecast period. As expected, the impacts on forecasted precipitation (relative to an ensemble of runs that do not utilize soil moisture information) tend to be localized over the small fraction of the earth with all of the required land and atmosphere properties.

A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products

USGS Publications Warehouse

Hansen, M.C.; Reed, B.

2000-01-01

Two global 1 km land cover data sets derived from 1992-1993 Advanced Very High Resolution Radiometer (AVHRR) data are currently available, the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover and the University of Maryland (UMd) 1 km land cover maps. This paper makes a preliminary comparison of the methodologies and results of the two products. The DISCover methodology employed an unsupervised clustering classification scheme on a per-continent basis using 12 monthly maximum NDVI composites as inputs. The UMd approach employed a supervised classification tree method in which temporal metrics derived from all AVHRR bands and the NDVI were used to predict class membership across the entire globe. The DISCover map uses the IGBP classification scheme, while the UMd map employs a modified IGBP scheme minus the classes of permanent wetlands, cropland/natural vegetation mosaic and ice and snow. Global area totals of aggregated vegetation types are very similar and have a per-pixel agreement of 74%. For tall versus short/no vegetation, the per-pixel agreement is 84%. For broad vegetation types, core areas map similarly, while transition zones around core areas differ significantly. This results in high regional variability between the maps. Individual class agreement between the two 1 km maps is 49%. Comparison of the maps at a nominal 0.5 resolution with two global ground-based maps shows an improvement of thematic concurrency of 46% when viewing average class agreement. The absence of the cropland mosaic class creates a difficulty in comparing the maps, due to its significant extent in the DISCover map. The DISCover map, in general, has more forest, while the UMd map has considerably more area in the intermediate tree cover classes of woody savanna/ woodland and savanna/wooded grassland.

Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research

USGS Publications Warehouse

Young, Steven

2017-05-02

When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.

Annual and seasonal distribution of day and night Land Surface Temperature trend over Greece.

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Gemitzi, A.; Eleftheriou, D.; Kalea, A.; Kalmintzis, G.; Kiachidis, K.; Koumadoraki, P.; Mpantasis, C.; Spathara, M. E.; Tsolaki, A.; Tzampazidou, M. I.

2017-12-01

Climate change is one of the most challenging research topics during the last few decades, as temperature rise has already posed a significant impact on earth's functions affecting thus all life of the planet. The present study investigates the distribution of day and night Land Surface Temperature (LST) trends over Greece, a country in Mediterranean area which is identified as one of the main ``hot-spots" of climate change projections. Remotely sensed LST data were obtained from MODIS sensor in the form of 8-day composites of day and night values at a resolution of 1km for a 17-year period, i.e. from 2000 to 2017. Spatial aggregates of 10km x 10km were computed and the annual and seasonal temporal trends were determined for each one of those sub-areas. Results showed that annual trends of daily LST in the majority of areas demonstrated decrease ranging from -1*10-2 oC to -1.3*10-3 oC, with some sporadic parts showing a slight increase. A totally different outcome is observed in the fate of night LST, with all areas over Greece demonstrating increasing annual trends ranging from 4.6 * 10-5 oC to 3.1 * 10-3 oC, with highest values in the South-East parts of the country. Seasonal trends in day and night LST showed the same pattern, i.e., a general decrease in the day LST and a definite increase in night. An interesting finding is the increase in winter LST trends observed both for day and night LST, indicating that the absolute minimum annual LST observed during winter in Greece increases. Our results also indicate that the difference between the day and night LST is decreasing.

Characterization and source apportionment of PAHs from a highly urbanized river sediments based on land use analysis.

PubMed

Huang, Yanping; Liu, Min; Wang, Ruiqi; Khan, Saira Khalil; Gao, Dengzhou; Zhang, Yazhou

2017-10-01

The city-scale land use/land cover change derived by urbanization on the fates of PAHs is of great concerns recently. This study evaluated spatiotemporal variations and sources of PAHs from a highly urbanized river sediments in the Huangpu River, Shanghai. Results indicated that the concentrations of PAHs in the sediments varied greatly across locations and seasons. The concentration of Σ 16 PAHs in the dry season were 6 times higher than that in wet season. The mainstream and midstream of the Huangpu River were identified as the hotspots in both dry and wet seasons. However, 4-ring PAH compounds were dominated, contributing 42.41% ± 6.81% and 44.70 ± 7.73% in the dry and wet seasons, respectively. Multivariate statistical and land use analysis suggested that the main sources of PAHs derived from the cultivation, traffic and commercial activities. Buffer radii (<750 m) area with cultivated land, road/street and transportation and commercial and business facilities contributed significantly the PAHs in the sediment of the Huangpu River. Population density was also an important variable regulating the PAHs concentrations less than 750 m in the wet season. Risk assessment results revealed that the PAHs toxicity in the sediments was higher in dry season than in wet season. Overall, severe land use changes caused by rapid urbanization can contribute more amount of PAHs emission and complicated sources of PAHs, thus provide insights into the importance of land use types in indicating PAHs source. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different

Reforesting degraded lands may not restore hydrological conditions

NASA Astrophysics Data System (ADS)

Balcerak, Ernie

2013-12-01

By the 1980s, forest lands in the Himalayas in central Nepal had become severely degraded as people cleared land for pastures. This led to lowered soil infiltration capacities, resulting in increased surface runoff, soil erosion, and flooding during the rainy season.

Soil Bacterial Community Response to Differences in Agricultural Management along with Seasonal Changes in a Mediterranean Region

PubMed Central

Bevivino, Annamaria; Paganin, Patrizia; Bacci, Giovanni; Florio, Alessandro; Pellicer, Maite Sampedro; Papaleo, Maria Cristiana; Mengoni, Alessio; Ledda, Luigi; Fani, Renato; Benedetti, Anna; Dalmastri, Claudia

2014-01-01

Land-use change is considered likely to be one of main drivers of biodiversity changes in grassland ecosystems. To gain insight into the impact of land use on the underlying soil bacterial communities, we aimed at determining the effects of agricultural management, along with seasonal variations, on soil bacterial community in a Mediterranean ecosystem where different land-use and plant cover types led to the creation of a soil and vegetation gradient. A set of soils subjected to different anthropogenic impact in a typical Mediterranean landscape, dominated by Quercus suber L., was examined in spring and autumn: a natural cork-oak forest, a pasture, a managed meadow, and two vineyards (ploughed and grass covered). Land uses affected the chemical and structural composition of the most stabilised fractions of soil organic matter and reduced soil C stocks and labile organic matter at both sampling season. A significant effect of land uses on bacterial community structure as well as an interaction effect between land uses and season was revealed by the EP index. Cluster analysis of culture-dependent DGGE patterns showed a different seasonal distribution of soil bacterial populations with subgroups associated to different land uses, in agreement with culture-independent T-RFLP results. Soils subjected to low human inputs (cork-oak forest and pasture) showed a more stable bacterial community than those with high human input (vineyards and managed meadow). Phylogenetic analysis revealed the predominance of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes phyla with differences in class composition across the site, suggesting that the microbial composition changes in response to land uses. Taken altogether, our data suggest that soil bacterial communities were seasonally distinct and exhibited compositional shifts that tracked with changes in land use and soil management. These findings may contribute to future searches for bacterial bio-indicators of soil

A satellite-based climatology (1989-2012) of lake surface water temperature from AVHRR 1-km for Central European water bodies

NASA Astrophysics Data System (ADS)

Riffler, Michael; Wunderle, Stefan

2013-04-01

The temperature of lakes is an important parameter for lake ecosystems influencing the speed of physio-chemical reactions, the concentration of dissolved gazes (e.g. oxygen), and vertical mixing. Even small temperature changes might have irreversible effects on the lacustrine system due to the high specific heat capacity of water. These effects could alter the quality of lake water depending on parameters like lake size and volume. Numerous studies mention lake water temperature as an indicator of climate change and in the Global Climate Observing System (GCOS) requirements it is listed as an essential climate variable. In contrast to in situ observations, satellite imagery offers the possibility to derive spatial patterns of lake surface water temperature (LSWT) and their variability. Moreover, although for some European lakes long in situ time series are available, the temperatures of many lakes are not measured or only on a non-regular basis making these observations insufficient for climate monitoring. However, only few satellite sensors offer the possibility to analyze time series which cover more than 20 years. The Advanced Very High Resolution Radiometer (AVHRR) is among these and has been flown on the National Oceanic and Atmospheric Administration (NOAA) Polar Operational Environmental Satellites (POES) and on the Meteorological Operational Satellites (MetOp) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) as a heritage instrument for almost 35 years. It will be carried on for at least ten more years finally offering a unique opportunity for satellite-based climate studies. Herein we present the results from a study initiated by the Swiss GCOS office to generate a satellite-based LSWT climatology for the pre-alpine water bodies in Switzerland. It relies on the extensive AVHRR 1-km data record (1985-2012) of the Remote Sensing Research Group at the University of Bern (RSGB) and has been derived from the AVHRR/2

Seasonality of Arctic Mediterranean Exchanges

NASA Astrophysics Data System (ADS)

Rieper, Christoph; Quadfasel, Detlef

2015-04-01

The Arctic Mediterranean communicates through a number of passages with the Atlantic and the Pacific Oceans. Most of the volume exchange happens at the Greenland-Scotland-Ridge: warm and saline Atlantic Water flows in at the surface, cold, dense Overflow Water flows back at the bottom and fresh and cold Polar Water flows out along the East Greenland coast. All surface inflows show a seasonal signal whereas only the outflow through the Faroe Bank Channel exhibits significant seasonality. Here we present a quantification of the seasonal cycle of the exchanges across the Greenland-Scotland ridge based on volume estimates of the in- and outflows within the last 20 years (ADCP and altimetry). Our approach is comparatistic: we compare different properties of the seasonal cycle like the strength or the phase between the different in- and outflows. On the seasonal time scale the in- and outflows across the Greenland-Scotland-Ridge are not balanced. The net flux thus has to be balanced by the other passages on the Canadian Archipelago, Bering Strait as well as runoff from land.

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

Seasonality and dietary requirements: will eating seasonal food contribute to health and environmental sustainability?

PubMed

Macdiarmid, Jennie I

2014-08-01

Eating more seasonal food is one proposal for moving towards more sustainable consumption patterns, based on the assumption that it could reduce the environmental impact of the diet. The aim of the present paper is to consider the implications of eating seasonal food on the different elements of sustainability (i.e. health, economics, society), not just the environment. Seasonality can be defined as either globally seasonal (i.e. produced in the natural production season but consumed anywhere in the world) or locally seasonal (i.e. produced in the natural production season and consumed within the same climatic zone). The environmental, health, economic and societal impact varies by the definition used. Global seasonality has the nutritional benefit of providing a more varied and consistent supply of fresh produce year round, but this increases demand for foods that in turn can have a high environmental cost in the country of production (e.g. water stress, land use change with loss of biodiversity). Greenhouse gas emissions of globally seasonal food are not necessarily higher than food produced locally as it depends more on the production system used than transportation. Eating more seasonal food, however, is only one element of a sustainable diet and should not overshadow some of the potentially more difficult dietary behaviours to change that could have greater environmental and health benefits (e.g. reducing overconsumption or meat consumption). For future guidelines for sustainable diets to be realistic they will need to take into account modern lifestyles, cultural and social expectations in the current food environment.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests

Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

NASA Astrophysics Data System (ADS)

Karlsson, Karl-Göran; Håkansson, Nina

2018-02-01

The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts

Changes in Land Use Intensity Within the Don and Dnieper River Basins Following the Collapse of the Soviet Union as Revealed by Spatio-temporal Trend Analysis

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G.

2007-12-01

We analyzed changes in trends of land surface phenology (LSP) within two major river basins in Western Eurasia. The basins of Don and Dnieper Rivers extend over 862,000 ha and include 17% of the impounded water surface area in the former Soviet Union. Major changes in agricultural practices occurring after 1991 led to some time drastic reductions in the cultivated area receiving fertilizers and the amount of water consumed for irrigation in addition to other macro-indicators of agricultural sector land use intensity. Image time series analysis can localize the extent, direction, and intensity of changes during the 1990s. Using vegetation index data from the AVHRR PAL and GIMMS datasets from 1982-1988 (Soviet period) and 1995-2000 (post-Soviet period) coupled with contemporary land cover maps from MODIS, we identified the spatial extent of temporal trends and assess their significance using seasonal Mann-Kendall tests adjusted for first-order autocorrelation. Roughly 90% of croplands and forested land in Dnieper Basin exhibited no significant trends during the Soviet period. The Don Basin had more significant positive trends during the Soviet period than the Dnieper Basin. There was a substantial disagreement between datasets on the extent of significant positive trends in Don croplands (35% for GIMMS vs. 8% for PAL) and in Don forests during Soviet period (38% for GIMMS vs. 27% for PAL). Although very little area in either basins showed significant negative trends during the Soviet period, substantial areas fell under significant negative trends during the post-Soviet period. We also found major disagreement on extent of significant negative trends in Don forests during post-Soviet period (6% for GIMMS vs. 24% for PAL). Even though, there are some significant disagreements between the datasets, there is no evidence of a consistent bias in the change analysis. Changes in irrigation water use may account for some of the changes in trend direction.

The Potential for Predicting Precipitation on Seasonal-to-Interannual Timescales

NASA Technical Reports Server (NTRS)

Koster, R. D.

1999-01-01

The ability to predict precipitation several months in advance would have a significant impact on water resource management. This talk provides an overview of a project aimed at developing this prediction capability. NASA's Seasonal-to-Interannual Prediction Project (NSIPP) will generate seasonal-to-interannual sea surface temperature predictions through detailed ocean circulation modeling and will then translate these SST forecasts into forecasts of continental precipitation through the application of an atmospheric general circulation model and a "SVAT"-type land surface model. As part of the process, ocean variables (e.g., height) and land variables (e.g., soil moisture) will be updated regularly via data assimilation. The overview will include a discussion of the variability inherent in such a modeling system and will provide some quantitative estimates of the absolute upper limits of seasonal-to-interannual precipitation predictability.

Tropical Carbon Response to Seasonal Phasing and Intensity of Precipitation in CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Basile, S.; Keppel-Aleks, G.

2016-12-01

Carbon cycling and water fluxes are connected over land. Understanding the current sensitivity of tropical ecosystems to climate drivers, such as precipitation, at short timescales is important for projecting future trends in the land sink of anthropogenic CO2. Several recent studies have shown that interannual droughts in 2005 and 2010 reduced net carbon uptake in the Amazon rainforest. In 2011 Southern Hemisphere semi-arid regions, especially Australian ecosystems, were found to largely contribute to the above average increase in the land carbon sink following consecutive wet seasons under La Nina conditions. Earth system models (ESMs) are able to simulate these sensitivities with varying degrees of fidelity, and ESMs also show a wide range of changes in precipitation phasing and intensity by 2100. Unsurprisingly, model projections of the land carbon sink also vary widely, with some simulations showing land becoming a CO2 source to the atmosphere. To constrain projections of the tropical land carbon balance among an ensemble of ESMs, we analyzed seasonal and interannual precipitation-carbon relationships in Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs for the period from 1982-2006. The sensitivity of net biospheric production on land (NBP) to precipitation was quantified on seasonal and annual timescales, and NBP was spatially correlated to precipitation across tropical and subtropical regions (+/- 30 degrees) within humid and semi-arid ecosystems. This analysis was expanded to soil moisture and drought metrics were used to distinguish between wet and dry seasons. Large scale precipitation was used to resolve Intertropical Convergence Zone (ITCZ) movement and convective precipitation was used to diagnose the short-term NBP response within the wet season. Results revealed a spread in NBP sensitivity to precipitation intensity as well as how individual models simulated precipitation phasing across different tropical regions.

Characteristics of the fractional cloud cover and its altitude distribution over the Indian Ocean region derived from NOAA14-AVHRR

NASA Astrophysics Data System (ADS)

Suresh Raju, C.; Rajeev, K.; Parameswaran, K.

The climatic impact of clouds and their role in energy and radiation budget of earth-atmosphere system largely depends on the cloud properties and its altitude of occurrence. The quantitative estimates of spatio-temporal variations of cloud fraction and cloud properties are limited over the tropical Indian Oceanic region. Cloudiness and its radiative properties over this region is significantly different from other tropical regions indicating the need for their detailed studies. This has an important role in the Indian summer monsoon which is also a part of the global climate system. Daily, monthly, seasonal and yearly mean frequency of occurrence of total and high altitude clouds are derived from the brightness temperature (TB) obtained from NOAA14-AVHRR data during the period of 1996-1999, and their spatio-temporal variations are investigated. The inversion algorithm used here is similar to the CLIVAR algorithm applied by ISCCP. All clouds with TB quad < 250 K are classified as high clouds, as their altitude of occurrence will be above ˜ 6 km. The clouds above ˜ 10 km (with TB<220K) are also classified separately to study the deep convective events. The geographical distribution of monthly, seasonal and annual mean frequency of occurrence of total cloud (Ftot) and high cloud (Fh) are remarkably consistent from year to year, though the absolute magnitude of the frequency of occurrence can vary by as much as 30%. The highest annual variations in Ftot and Fh are observed near the eastern parts of Bay of Bengal. The average amplitude of the annual cycle in Ftot in this region is ˜ 40%. During the south-west monsoon season, the monthly mean of Ftot shows very large spatial gradients in the western Arabian Sea. In July, the Ftot varies from less than 20% near Arabian coastal regions to more than 75% at a location 10 degrees east of the Arabian coast. Similar gradients in Ftot are also observed between the equator and 10 S. One of the very striking features in Ftot

BOREAS RSS-7 Regional LAI and FPAR Images From 10-Day AVHRR-LAC Composites

NASA Technical Reports Server (NTRS)

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

2000-01-01

The BOReal Ecosystem-Atmosphere Study Remote Sensing Science (BOREAS RSS-7) team collected various data sets to develop and validate an algorithm to allow the retrieval of the spatial distribution of Leaf Area Index (LAI) from remotely sensed images. Advanced Very High Resolution Radiometer (AVHRR) level-4c 10-day composite Normalized Difference Vegetation Index (NDVI) images produced at CCRS were used to produce images of LAI and the Fraction of Photosynthetically Active Radiation (FPAR) absorbed by plant canopies for the three summer IFCs in 1994 across the BOREAS region. The algorithms were developed based on ground measurements and Landsat Thematic Mapper (TM) images. The data are stored in binary image format files.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

The effect of surface anisotropy and viewing geometry on the estimation of NDVI from AVHRR

USGS Publications Warehouse

Meyer, David; Verstraete, M.; Pinty, B.

1995-01-01

Since terrestrial surfaces are anisotropic, all spectral reflectance measurements obtained with a small instantaneous field of view instrument are specific to these angular conditions, and the value of the corresponding NDVI, computed from these bidirectional reflectances, is relative to the particular geometry of illumination and viewing at the time of the measurement. This paper documents the importance of these geometric effects through simulations of the AVHRR data acquisition process, and investigates the systematic biases that result from the combination of ecosystem-specific anisotropies with instrument-specific sampling capabilities. Typical errors in the value of NDVI are estimated, and strategies to reduce these effects are explored. -from Authors

Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions

USGS Publications Warehouse

Schilling, Keith E.; Jha, Manoj K.; Zhang, You‐Kuan; Gassman, Philip W.; Wolter, Calvin F.

2009-01-01

Over the last century, land use and land cover (LULC) in the United States Corn Belt region shifted from mixed perennial and annual cropping systems to primarily annual crops. Historical LULC change impacted the annual water balance in many Midwestern basins by decreasing annual evapotranspiration (ET) and increasing streamflow and base flow. Recent expansion of the biofuel industry may lead to future LULC changes from increasing corn acreage and potential conversion of the industry to cellulosic bioenergy crops of warm or cool season grasses. In this paper, the Soil and Water Assessment Tool (SWAT) model was used to evaluate potential impacts from future LULC change on the annual and seasonal water balance of the Raccoon River watershed in west‐central Iowa. Three primary scenarios for LULC change and three scenario variants were evaluated, including an expansion of corn acreage in the watershed and two scenarios involving expansion of land using warm season and cool season grasses for ethanol biofuel. Modeling results were consistent with historical observations. Increased corn production will decrease annual ET and increase water yield and losses of nitrate, phosphorus, and sediment, whereas increasing perennialization will increase ET and decrease water yield and loss of nonpoint source pollutants. However, widespread tile drainage that exists today may limit the extent to which a mixed perennial‐annual land cover would ever resemble pre‐1940s hydrologic conditions. Study results indicate that future LULC change will affect the water balance of the watershed, with consequences largely dependent on the future LULC trajectory.

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products

PubMed Central

Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

2017-01-01

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI

Comparison and Evaluation of Annual NDVI Time Series in China Derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 Products.

PubMed

Guo, Xiaoyi; Zhang, Hongyan; Wu, Zhengfang; Zhao, Jianjun; Zhang, Zhengxiang

2017-06-06

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI datasets (MOD13C1) are compared and evaluated for the period from 2001 to 2014 in China. The spatial patterns of the NDVI generally match between the LTDR V4 and MOD13C1 datasets. The transitional zone between high and low NDVI values generally matches the boundary of semi-arid and sub-humid regions. A significant and high coefficient of determination is found between the two datasets according to a pixel-based correlation analysis. The spatially averaged NDVI of LTDR V4 is characterized by a much weaker positive regression slope relative to that of the spatially averaged NDVI of the MOD13C1 dataset because of changes in NOAA AVHRR sensors between 2005 and 2006. The measured NDVI values of LTDR V4 were always higher than that of MOD13C1 in western China due to the relatively lower atmospheric water vapor content in western China, and opposite observation appeared in eastern China. In total, 18.54% of the LTDR V4 NDVI pixels exhibit significant trends, whereas 35.79% of the MOD13C1 NDVI pixels show significant trends. Good agreement is observed between the significant trends of the two datasets in the Northeast Plain, Bohai Economic Rim, Loess Plateau, and Yangtze River Delta. By contrast, the datasets contrasted in northwestern desert regions and southern China. A trend analysis of the regression slope values according to the vegetation type shows good agreement between the LTDR V4 and MOD13C1 datasets. This study demonstrates the spatial and temporal consistencies and discrepancies between the AVHRR LTDR and MODIS MOD13C1 NDVI

Reconciling top-down and bottom-up estimates of CO2 fluxes to understand increased seasonal exchange in Northern ecosystems

NASA Astrophysics Data System (ADS)

Bastos, A.; Ciais, P.; Zhu, D.; Maignan, F.; Wang, X.; Chevallier, F.; Ballantyne, A.

2017-12-01

Continuous atmospheric CO2 monitoring data indicate enhanced seasonal exchange in the high-latitudes in the Northern Hemisphere (above 40oN), mainly attributed to terrestrial ecosystems. Whether this enhancement is mostly explained by increased vegetation growth due to CO2 fertilization and warming, or by changes in land-use and land-management practices is still an unsettled question (e.g. Forkel et al. (2016) and Zeng et al. (2013)). Previous studies have shown that models present variable performance in capturing trends in CO2 amplitude at CO2 monitoring sites, and that Earth System Models present large spread in their estimates of such trends. Here we integrate data of atmospheric CO2 exchange in terrestrial ecosystems by a set of atmospheric CO2 inversions and a range of land-surface models to evaluate the ability of models to reproduce changes in CO2 seasonal exchange within the observation uncertainty. We then analyze the factors that explain the model spread to understand if the trend in seasonal CO2 amplitude may indeed be a useful metric to constrain future changes in terrestrial photosynthesis (Wenzel et al., 2016). We then compare model simulations with satellite and other observation-based datasets of vegetation productivity, biomass stocks and land-cover change to test the contribution of natural (CO2 fertilization, climate) and human (land-use change) factors to the increasing trend in seasonal CO2 amplitude. Forkel, Matthias, et al. "Enhanced seasonal CO2 exchange caused by amplified plant productivity in northern ecosystems." Science 351.6274 (2016): 696-699. Wenzel, Sabrina, et al. "Projected land photosynthesis constrained by changes in the seasonal cycle of atmospheric CO2." Nature 538, no. 7626 (2016): 499-501.Zeng, Ning, et al. "Agricultural Green Revolution as a driver of increasing atmospheric CO2 seasonal amplitude." Nature 515.7527 (2014): 394.

Characterization of land surface energy fluxes in a tropical lowland rice paddy

NASA Astrophysics Data System (ADS)

Chatterjee, Dibyendu; Tripathi, Rahul; Chatterjee, Sumanta; Debnath, Manish; Shahid, Mohammad; Bhattacharyya, Pratap; Swain, Chinmaya Kumar; Tripathy, Rojalin; Bhattacharya, Bimal K.; Nayak, Amaresh Kumar

2018-04-01

A field experiment was conducted in 2015 to study the land surface energy fluxes from tropical lowland rice paddy in eastern India with an objective to determine the mass, momentum, and energy exchange rates between rice paddies and the atmosphere. All the land surface energy fluxes were measured by eddy covariance (EC) system (make Campbell Scientific) in dry season (DS, 1-125 Julian days), dry fallow (DF, 126-181 Julian days), wet season (WS, 182-324 Julian days), and wet fallow (WF, 325-365 Julian days). The rice was cultivated in dry season (January-May) and wet season (July-November) in low wet lands and the ground is kept fallow during the remainder of the year. Results showed that albedo varied from 0.09 to 0.24 and showed positive value from morning 6:00 h until evening 18:00 h. Mean soil temperature (T g) was highest in DF, while the skin temperature (T s) was highest in WS. Average Bowen ratio (B) ranged from 0.21 to 0.64 and large variation in B was observed during the fallow periods as compared to the cropping seasons. The magnitude of aerodynamic, canopy, and climatological resistances increased with the progress of cropping season and their magnitudes decreased during the end of both cropping seasons and found minimum during the fallow periods. At a constant vapor pressure deficit (VPD) at 0.16, 0.18, 0.15, and 0.43 kPa, latent heat flux (LE) initially increased, but later it tended to level off with an increase in VPD. The actual evapotranspiration (ETa) during both the cropping seasons was higher than the fallow period. This study can be used as a source of default values for many land surface energy fluxes which are required in various meteorological or air-quality models for rice paddies. A larger imbalance of energy was observed during the wet season as the energy is stored and perhaps advected in the fresh water.

Midwest Agriculture: A comparison of AVHRR NDVI3g data and crop yields in Corn Belt region of the United States from 1982 to 2014

NASA Astrophysics Data System (ADS)

Glennie, E.; Anyamba, A.; Eastman, R.

2016-12-01

A time series of Advanced Very High Resolution Radiometer (AVHRR) derived normalized difference vegetation index (NDVI) images was compared to National Agricultural Statistics Service (NASS) corn yield data in the Corn Belt of the United States from 1982 to 2014. The relationship between NDVI and crop yields under El Nino, neutral, and La Nina conditions was used to assess 1) the reliability of using NDVI as an indicator of crop productivity, and 2) the response of the Corn Belt to El Nino/ Southern Oscillation (ENSO) teleconnection effects. First, bi-monthly NDVI data were combined into monthly data using the maximum value compositing technique to reduce cloud contamination and other effects. The most representative seasonal curve of NDVI values over the course of the study period was extracted to define the growing season in the region - May to October. Standardized NDVI anomalies were calculated and averaged to produce a growing season NDVI metrics to represent each Agricultural Statistics Division (ASD) for each year in the study period. The corn yields were detrended in order to remove effects of technological advancements on crop productivity (use of genetically modified seeds, fertilizer, herbicides). Correlation (R) values between the NDVI anomalies and detrended corn yields varied across the Corn Belt, with a maximum of 0.81 and mean of 0.49. While corn is the dominant crop in the region, some inconsistencies between corn yield and NDVI may be accounted for by an increase in soy yield for a given year due to crop rotation practices. The 10 El Nino events and 9 La Nina events that occurred between 1982 and 2014 are not reflected in a consistent manner in NDVI or corn yield data. However, composites of NDVI and crop yields for all El Nino events indicate there is a tendency for higher than normal NDVI and increased corn yields. Conversely, the composite crop yield image for La Nina events shows a slight decrease in productivity.

Outdoors America: recreational opportunities on public lands

USGS Publications Warehouse

,

1998-01-01

This Federal Recreation Lands map is a consolidated guide to public lands offering outdoor recreation opportunities. Some areas have more recreation potential than others, and types of recreation available may vary from place to place. Many areas include private land not open to the public. Care should be taken to respect the rights of private property owners. For information regarding specific activities, services, facilities, hours and seasons of operation, entrance and other user fees, and accessibility, contact the appropriate agency office.

Seasonal Cycles in Curiosity First Two Martian Years

NASA Image and Video Library

2016-05-11

By monitoring weather throughout two Martian years since landing in Gale Crater in 2012, NASA Curiosity Mars rover has documented seasonal patterns such as shown in these graphs of temperature, water-vapor content and air pressure.

Variability and Predictability of Land-Atmosphere Interactions: Observational and Modeling Studies

NASA Technical Reports Server (NTRS)

Roads, John; Oglesby, Robert; Marshall, Susan; Robertson, Franklin R.

2002-01-01

The overall goal of this project is to increase our understanding of seasonal to interannual variability and predictability of atmosphere-land interactions. The project objectives are to: 1. Document the low frequency variability in land surface features and associated water and energy cycles from general circulation models (GCMs), observations and reanalysis products. 2. Determine what relatively wet and dry years have in common on a region-by-region basis and then examine the physical mechanisms that may account for a significant portion of the variability. 3. Develop GCM experiments to examine the hypothesis that better knowledge of the land surface enhances long range predictability. This investigation is aimed at evaluating and predicting seasonal to interannual variability for selected regions emphasizing the role of land-atmosphere interactions. Of particular interest are the relationships between large, regional and local scales and how they interact to account for seasonal and interannual variability, including extreme events such as droughts and floods. North and South America, including the Global Energy and Water Cycle Experiment Continental International Project (GEWEX GCIP), MacKenzie, and LBA basins, are currently being emphasized. We plan to ultimately generalize and synthesize to other land regions across the globe, especially those pertinent to other GEWEX projects.

Seasonal habitat use and selection by grizzly bears in Northern British Columbia

USGS Publications Warehouse

Milakovic, B.; Parker, K.L.; Gustine, D.D.; Lay, R.J.; Walker, A.B.D.; Gillingham, M.P.

2012-01-01

We defined patterns of habitat use and selection by female grizzly bears (Ursus arctos) in the Besa-Prophet watershed of northern British Columbia. We fitted 13 adult females with Geographic Positioning System (GPS) radio-collars and monitored them between 2001 and 2004. We examined patterns of habitat selection by grizzly bears relative to topographical attributes and 3 potential surrogates of food availability: land-cover class, vegetation biomass or quality (as measured by the Normalized Difference Vegetation Index), and selection value for prey species themselves (moose [Alces alces], elk [Cervus elaphus], woodland caribou [Rangifer tarandus], Stone's sheep [Ovis dalli stonei]). Although vegetation biomass and quality, and selection values for prey were important in seasonal selection by some individual bears, land-cover class, elevation, aspect, and vegetation diversity most influenced patterns of habitat selection across grizzly bears, which rely on availability of plant foods and encounters with ungulate prey. Grizzly bears as a group avoided conifer stands and areas of low vegetation diversity, and selected for burned land-cover classes and high vegetation diversity across seasons. They also selected mid elevations from what was available within seasonal ranges. Quantifying relative use of different attributes helped place selection patterns within the context of the landscape. Grizzly bears used higher elevations (1,595??31 m SE) in spring and lower elevations (1,436??27 m) in fall; the range of average elevations used among individuals was highest (500 m) during the summer. During all seasons, grizzly bears most frequented aspects with high solar gain. Use was distributed across 10 land-cover classes and depended on season. Management and conservation actions must maintain a diverse habitat matrix distributed across a large elevational gradient to ensure persistence of grizzly bears as levels of human access increase in the northern Rocky Mountains

Effects of seasonality and land-use change on carbon and water fluxes across the Amazon basin: synthesizing results from satellite-based remote sensing, towers, and models

NASA Astrophysics Data System (ADS)

Saleska, S.; Goncalves, L. G.; Baker, I.; Costa, M.; Poulter, B.; Christoffersen, B.; Da Rocha, H. R.; Didan, K.; Huete, A.; Imbuziero, H.; Kruijt, B.; Manzi, A.; von Randow, C.; Restrepo-Coupe, N.; Silva, R.; Tota, J.; Denning, S.; Gulden, L.; Rosero, E.; Zeng, X.

2008-12-01

Amazon forests play an important and complex role in the global carbon cycle, and important advances have been made in understanding Amazon processes in recent years. However, reconciling modeled mechanisms of carbon cycling with observations across scales remains a challenge. To better address this challenge, we initiated a Model intercomparison Project for the 'Large-Scale Biosphere Atmosphere Experiment in Amazonia' (LBA-MIP) to integrate modeling and observational studies for improved understanding of Amazon basin carbon cycling. Here, we report on the initial results of this project, which used the network of meteorological and climate data (sunlight, radiation, precipitation) from Amazon tower sites in forest and converted lands to drive a suite of 20 ecosystem models that simulate energy, water and CO2 fluxes. We compared model mechanisms to each other and to the relevant flux observations from those towers, as well as from satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). Remote sensing and flux tower observations tend to show higher primary forest photosynthetic activity in the dry season than in the wet season in central Amazon, a broad pattern that is now captured in many models, but for different reasons. A reversal from the primary forest pattern was observed in areas converted to pasture, agriculture, or secondary forests, likely a consequence of the elimination of deep root access to deep soil waters which often persist through the dry season. Testing the models with observed fluxes under different land use patterns, and across different spatial scales with remote sensing, is enabling us to distinguish correct vs. incorrect model mechanisms and improve understanding of Amazon processes.

Recent History of Large-Scale Ecosystem Disturbances in North America Derived from the AVHRR Satellite Record

NASA Technical Reports Server (NTRS)

Potter, Christopher; Tan, Pang-Ning; Kumar, Vipin; Kicharik, Chris; Klooster, Steven; Genovese, Vanessa

2004-01-01

Ecosystem structure and function are strongly impacted by disturbance events, many of which in North America are associated with seasonal temperature extremes, wildfires, and tropical storms. This study was conducted to evaluate patterns in a 19-year record of global satellite observations of vegetation phenology from the Advanced Very High Resolution Radiometer (AVHRR) as a means to characterize major ecosystem disturbance events and regimes. The fraction absorbed of photosynthetically active radiation (FPAR) by vegetation canopies worldwide has been computed at a monthly time interval from 1982 to 2000 and gridded at a spatial resolution of 8-km globally. Potential disturbance events were identified in the FPAR time series by locating anomalously low values (FPAR-LO) that lasted longer than 12 consecutive months at any 8-km pixel. We can find verifiable evidence of numerous disturbance types across North America, including major regional patterns of cold and heat waves, forest fires, tropical storms, and large-scale forest logging. Summed over 19 years, areas potentially influenced by major ecosystem disturbances (one FPAR-LO event over the period 1982-2000) total to more than 766,000 km2. The periods of highest detection frequency were 1987-1989, 1995-1997, and 1999. Sub- continental regions of Alaska and Central Canada had the highest proportion (greater than 90%) of FPAR-LO pixels detected in forests, tundra shrublands, and wetland areas. The Great Lakes region showed the highest proportion (39%) of FPAR-LO pixels detected in cropland areas, whereas the western United States showed the highest proportion (16%) of FPAR-LO pixels detected in grassland areas. Based on this analysis, an historical picture is emerging of periodic droughts and heat waves, possibly coupled with herbivorous insect outbreaks, as among the most important causes of ecosystem disturbance in North America.

Future of Land Remote Sensing: What is Needed

NASA Technical Reports Server (NTRS)

Goward, Samuel N.

2007-01-01

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

Modelling seasonal meltwater forcing of the velocity of land-terminating margins of the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Koziol, Conrad P.; Arnold, Neil

2018-03-01

Surface runoff at the margin of the Greenland Ice Sheet (GrIS) drains to the ice-sheet bed, leading to enhanced summer ice flow. Ice velocities show a pattern of early summer acceleration followed by mid-summer deceleration due to evolution of the subglacial hydrology system in response to meltwater forcing. Modelling the integrated hydrological-ice dynamics system to reproduce measured velocities at the ice margin remains a key challenge for validating the present understanding of the system and constraining the impact of increasing surface runoff rates on dynamic ice mass loss from the GrIS. Here we show that a multi-component model incorporating supraglacial, subglacial, and ice dynamic components applied to a land-terminating catchment in western Greenland produces modelled velocities which are in reasonable agreement with those observed in GPS records for three melt seasons of varying melt intensities. This provides numerical support for the hypothesis that the subglacial system develops analogously to alpine glaciers and supports recent model formulations capturing the transition between distributed and channelized states. The model shows the growth of efficient conduit-based drainage up-glacier from the ice sheet margin, which develops more extensively, and further inland, as melt intensity increases. This suggests current trends of decadal-timescale slowdown of ice velocities in the ablation zone may continue in the near future. The model results also show a strong scaling between average summer velocities and melt season intensity, particularly in the upper ablation area. Assuming winter velocities are not impacted by channelization, our model suggests an upper bound of a 25 % increase in annual surface velocities as surface melt increases to 4 × present levels.

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

Land Surface Phenologies of the Northern Great Plains: Possible Futures Arising From Land and Climate Change

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Wimberly, M. C.; Senay, G.; Wang, A.; Chang, J.; Wright, C. R.; Hansen, M. C.

2008-12-01

Land cover change across the Northern Great Plains of North America over the past three decades has been driven by changes in agricultural management (conservation tillage; irrigation), government incentives (Conservation Reserve Program; subsidies to grain-based ethanol), crop varieties (cold-hardy soybean), and market dynamics (increasing world demand). Climate change across the Northern Great Plains over the past three decades has been evident in trends toward earlier warmth in the spring and a longer frost-free season. Together these land and climate changes induce shifts in local and regional land surface phenologies (LSPs). Any significant shift in LSP may correspond to a significant shift in evapotranspiration, with consequences for regional hydrometeorology. We explored possible future scenarios involving land use and climate change in six steps. First, we defined the nominal draw areas of current and future biorefineries in North Dakota, South Dakota, Nebraska, Minnesota, and Iowa and masked those land cover types within the draw areas that were unlikely to change to agricultural use (open water, settlements, forests, etc.). Second, we estimated the proportion of corn and soybean remaining within the masked draw areas using MODIS-derived crop maps. Third, in each draw area, we modified LSPs to simulate crop changes for a control and two treatment scenarios. In the control, we used LSP profiles identified from MODIS Collection 5 NBAR data. In one treatment, we increased the proportion of tallgrass LSPs in the draw areas to represent widespread cultivation of a perennial cellulosic crop, like switchgrass. In a second treatment, we increased the proportion of corn LSPs in the draw areas to represent increased corn cultivation. Fourth, we characterized the seasonal progression of the thermal regime associated with the LSP profiles using MODIS Land Surface Temperature (LST) products. Fifth, we modeled the LSP profile as a quadratic function of accumulated

Cloud-property retrieval using merged HIRS and AVHRR data

NASA Technical Reports Server (NTRS)

Baum, Bryan A.; Wielicki, Bruce A.; Minnis, Patrick; Parker, Lindsay

1992-01-01

A technique is developed that uses a multispectral, multiresolution method to improve the overall retrieval of mid- to high-level cloud properties by combining HIRS sounding channel data with higher spatial resolution AVHRR radiometric data collocated with the HIRS footprint. Cirrus cloud radiative and physical properties are determined using satellite data, surface-based measurements provided by rawinsondes and lidar, and aircraft-based lidar data collected during the First International Satellite Cloud Climatology Program Regional Experiment in Wisconsin during the months of October and November 1986. HIRS cloud-height retrievals are compared to ground-based lidar and aircraft lidar when possible. Retrieved cloud heights are found to have close agreement with lidar for thin cloud, but are higher than lidar for optically thick cloud. The results of the reflectance-emittance relationships derived are compared to theoretical scattering model results for both water-droplet spheres and randomly oriented hexagonal ice crystals. It is found that the assumption of 10-micron water droplets is inadequate to describe the reflectance-emittance relationship for the ice clouds seen here. Use of this assumption would lead to lower cloud heights using the ISCCP approach. The theoretical results show that use of hexagonal ice crystal phase functions could lead to much improved results for cloud retrieval algorithms using a bispectral approach.

Biodiversity and Seasonal Changes of the Microbiome in Chernozem Agroecosystem

NASA Astrophysics Data System (ADS)

Kutovaya, Olga; Chernov, Timofey; Tkhakakhova, Azida; Ivanova, Ekaterina

2016-04-01

Studies of the influence of different agricultural technologies on the soil microbiome are widespread; they are important for understanding the dependence of the microbiome on environmental and soil factors and solution of practical problems related to the control of biochemical processes in soils used in agriculture. The seasonal variability (spring-summer-autumn) of the taxonomic structure of prokaryotic microbiomes in chernozems was studied using sequencing of the 16S rRNA gene. The DNA preparation was used as the matrix for a polymerase chain reaction with the use of a pair of universal primers to the variable region V4 of the 16S rRNA gene - F515 (GTGCCAGCMGCCGCGGTAA) and R806 (GGACTACVSGGGTATCTAAT). The preparation of the samples and sequencing were made on a GS Junior. The samples were collected from the topsoil (0-20 cm) horizons of a long-term fallow and croplands differing in the rates of application of mineral fertilizers (NPK). The results of the weighted UniFrac analysis show that the microbiomes of the fallow and field were distinctly distinguished and that the type of land use significantly affected the structure of the microbial community. The most sensitive to the type of land use were the representatives of the Firmicutes, Gemmatiomonades, and Verrucomicrobia phyla. The type of vegetation and aeration of the root-dwelling soil layer seem to be key factors of this influence. The microbiomes analyzed also differed by seasons: in the autumn samples, they were closer to the spring ones than to the summer ones. This fact evidences that the seasonal differences in the microbiomes are not simple gradual temporal changes; they reflect the influence of some ecological factors transforming the phylogenetic structure of prokaryotic communities. As the seasonal shift was equally expressed in the microbiomes of the field and fallow, it is logical to assume that it was caused by the factors common for two systems of land use. Statistically sensitive to seasonal

Observed Variation in Carbon and Water Exchange Across Crop Types, Seasons, and Years in Un-irrigated Land of the Southern Great Plains

NASA Astrophysics Data System (ADS)

Fischer, M. L.; Billesbach, D. P.; Riley, W. J.; Berry, J. A.; Torn, M. S.

2004-12-01

Accurate prediction of the regional responses of carbon and water fluxes to changing climate, land use, and management requires models that are parameterized and tested against measurements made in multiple land cover types and over seasonal and inter-annual time scales. In particular, modelers predicting fluxes for un-irrigated agriculture are posed with the additional challenge of characterizing the onset and severity of water stress. We report results from three years of an ongoing series of measurement campaigns that quantify the spatial heterogeneity of land surface-atmosphere exchanges of carbon dioxide, water, and energy. Eddy covariance flux measurements were made in pastures and dominant crop types surrounding the US-DOE Atmospheric Radiation Measurement Program central facility near Lamont, Oklahoma (36.605 N, 97.485 W). Ancillary measurements included radiation budget, meteorology, soil moisture and temperature, leaf area index, plant biomass, and plant and soil carbon and nitrogen content. Within a given year, the dominant spatial variation in fluxes of carbon, water, and energy are caused by variations of land cover due to the distinct phenology of winter-spring (winter wheat) versus summer crops (e.g., pasture, sorghum, soybeans). Within crop and yearly variations were smaller. In 2002, variations in net ecosystem carbon exchange (NEE), for three closely spaced winter wheat fields was 10-20%. Variations between years for the same crop types were also large. Net primary production (NPP) of winter wheat in the spring of 2003 versus 2002 increased by a factor of two, while NEE increased by 35%. The large increase in production and NEE are positively correlated with precipitation, integrated over the previous summer-fall periods. We discuss the implications of these results by extracting and comparing factors relevant for parameterization of land surface models and by comparing crop yield with historic variations in yield at the landscape scale.

Spatial scale of land-use impacts on riverine drinking source water quality

NASA Astrophysics Data System (ADS)

Hurley, Tim; Mazumder, Asit

2013-03-01

Drinking water purveyors are increasingly relying on land conservation and management to ensure the safety of the water that they provide to consumers. To cost-effectively implement any such landscape initiatives, resources must be targeted to the appropriate spatial scale to address quality impairments of concern in a cost-effective manner. Using data gathered from 40 Canadian rivers across four ecozones, we examined the spatial scales at which land use was most closely associated with drinking source water quality metrics. Exploratory linear mixed-effects models accounting for climatic, hydrological, and physiographic variation among sites suggested that different spatial areas of land-use influence drinking source water quality depending on the parameter and season investigated. Escherichia coli spatial variability was only associated with land use at a local (5-10 km) spatial scale. Turbidity measures exhibited a complex association with land use, suggesting that the land-use areas of greatest influence can range from a 1 km subcatchment to the entire watershed depending on the season. Total organic carbon concentrations were only associated with land use characterized at the entire watershed scale. The Canadian Council of Ministers of the Environment Water Quality Index was used to calculate a composite measure of seasonal drinking source water quality but did not provide additional information beyond the analyses of individual parameters. These results suggest that entire watershed management is required to safeguard drinking water sources with more focused efforts at targeted spatial scales to reduce specific risk parameters.

Modeling the hydrological impacts of land use/land cover changes in the Andassa watershed, Blue Nile Basin, Ethiopia.

PubMed

Gashaw, Temesgen; Tulu, Taffa; Argaw, Mekuria; Worqlul, Abeyou W

2018-04-01

Understanding the hydrological response of a watershed to land use/land cover (LULC) changes is imperative for water resources management planning. The objective of this study was to analyze the hydrological impacts of LULC changes in the Andassa watershed for a period of 1985-2015 and to predict the LULC change impact on the hydrological status in year 2045. The hybrid land use classification technique for classifying Landsat images (1985, 2000 and 2015); Cellular-Automata Markov (CA-Markov) for prediction of the 2030 and 2045 LULC states; the Soil and Water Assessment Tool (SWAT) for hydrological modeling were employed in the analyses. In order to isolate the impacts of LULC changes, the LULC maps were used independently while keeping the other SWAT inputs constant. The contribution of each of the LULC classes was examined with the Partial Least Squares Regression (PLSR) model. The results showed that there was a continuous expansion of cultivated land and built-up area, and withdrawing of forest, shrubland and grassland during the 1985-2015 periods, which are expected to continue in the 2030 and 2045 periods. The LULC changes, which had occurred during the period of 1985 to 2015, had increased the annual flow (2.2%), wet seasonal flow (4.6%), surface runoff (9.3%) and water yield (2.4%). Conversely, the observed changes had reduced dry season flow (2.8%), lateral flow (5.7%), groundwater flow (7.8%) and ET (0.3%). The 2030 and 2045 LULC states are expected to further increase the annual and wet season flow, surface runoff and water yield, and reduce dry season flow, groundwater flow, lateral flow and ET. The change in hydrological components is a direct result of the significant transition from the vegetation to non-vegetation cover in the watershed. This suggests an urgent need to regulate the LULC in order to maintain the hydrological balance. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of C-band and Ku-band scatterometry for medium-resolution tropical forest inventory

NASA Astrophysics Data System (ADS)

Hardin, Perry J.; Long, David G.

1993-08-01

Since 1978, AVHRR imagery from NOAA polar orbiters has provided coverage of tropical regions at this desirable resolution, but much of the imagery is plagued with heavy cloud cover typical of equatorial regions. Clearly a medium resolution radar sensor would be a useful addition to AVHRR, but none are planned to fly in the future. In contrast, scatterometers are an important radar component of many future earth remote sensing systems, but the inherent resolution of these instruments is too low (approximately equals 50 km) for monitoring earth's land surfaces. However, a recently developed image reconstruction technique can increase the spatial resolution of scatterometer data to levels (approximately equals 4 to 14 km) approaching AVHRR global area coverage (approximately equals 4 km). When reconstructed, scatterometer data may prove to be an important asset in evaluating equatorial land cover. In this paper, the authors compare the utility of reconstructed Seasat scatterometer (SASS), Ku-band microwave data to reconstructed ERS-1 C-band scatterometer imagery for discrimination and monitoring of tropical vegetation formations. In comparative classification experiments conducted on reconstructed images of Brasil, the ERS-1 C-band imagery was slightly superior to its reconstructed SASS Ku-band counterpart for discriminating between several equatorial land cover classes. A classification accuracy approaching .90 was achieved when the two scatterometer images were combined with an AVHRR normalized difference vegetation index (NDVI) image. The success of these experiments indicates that further research into reconstructed image applications to tropical forest monitoring is warranted.

GloFAS-Seasonal: Operational Seasonal Ensemble River Flow Forecasts at the Global Scale

NASA Astrophysics Data System (ADS)

Emerton, Rebecca; Zsoter, Ervin; Smith, Paul; Salamon, Peter

2017-04-01

Seasonal hydrological forecasting has potential benefits for many sectors, including agriculture, water resources management and humanitarian aid. At present, no global scale seasonal hydrological forecasting system exists operationally; although smaller scale systems have begun to emerge around the globe over the past decade, a system providing consistent global scale seasonal forecasts would be of great benefit in regions where no other forecasting system exists, and to organisations operating at the global scale, such as disaster relief. We present here a new operational global ensemble seasonal hydrological forecast, currently under development at ECMWF as part of the Global Flood Awareness System (GloFAS). The proposed system, which builds upon the current version of GloFAS, takes the long-range forecasts from the ECMWF System4 ensemble seasonal forecast system (which incorporates the HTESSEL land surface scheme) and uses this runoff as input to the Lisflood routing model, producing a seasonal river flow forecast out to 4 months lead time, for the global river network. The seasonal forecasts will be evaluated using the global river discharge reanalysis, and observations where available, to determine the potential value of the forecasts across the globe. The seasonal forecasts will be presented as a new layer in the GloFAS interface, which will provide a global map of river catchments, indicating whether the catchment-averaged discharge forecast is showing abnormally high or low flows during the 4-month lead time. Each catchment will display the corresponding forecast as an ensemble hydrograph of the weekly-averaged discharge forecast out to 4 months, with percentile thresholds shown for comparison with the discharge climatology. The forecast visualisation is based on a combination of the current medium-range GloFAS forecasts and the operational EFAS (European Flood Awareness System) seasonal outlook, and aims to effectively communicate the nature of a seasonal

Methodology for interpretation of SST retrievals using the AVHRR split window algorithm

NASA Technical Reports Server (NTRS)

Barbieri, R. W.; Mcclain, C. R.; Endres, D. L.

1983-01-01

Intercomparisons of sea surface temperature (SST) products derived from the operational NOAA-7 AVHRR-II algorithm and in situ observations are made. The 1982 data sets consist of ship survey data during the winter from the Mid-Atlantic Bight (MAB), ship and buoy measurements during April and September in the Gulf of Mexico and shipboard observations during April off the N.W. Spanish coast. The analyses included single pixel comparisons and the warmest pixel technique for 2 x 2 pixel and 10 x 10 pixel areas. The reason for using multi-pixel areas was for avoiding cloud contaminated pixels in the vicinity of the field measurements. Care must be taken when applying the warmest pixel technique near oceanic fronts. The Gulf of Mexico results clearly indicate a persistent degradation in algorithm accuracy due to El Chichon aerosols. The MAB and Spanish data sets indicate that very accurate estimates can be achieved if care is taken to avoid clouds and oceanic fronts.

A land management history for central Queensland, Australia as determined from land-holder questionnaire and aerial photography.

PubMed

Fensham, Roderick J; Fairfax, Russell J

2003-08-01

Features of the land management history over a 125,755 km(2) area of central Queensland, Australia were determined from a variety of sources. A random sample of 205 site locations provided the basis for determining trends in land use. Trends in vegetation clearing were determined using sequential aerial photography for the sample sites, revealing a steady rate averaging nearly 1% of the region per annum over 41 years. This measure of sustained clearing over a large region is higher than recently published clearing rates from South America. Land types have been selectively cleared with over 90% of the Acacia on clay land type having been cleared. A land-holder questionnaire pertaining to the random sites yielded a response rate of 71% and provided information on vegetation clearing, ploughing, tree killing (ring-barking or tree poisoning), and fire frequency, season and intensity. The land-holder responses were compared with independent data sources where possible and revealed no mis-information. However, land-holders may have been marginally less likely to respond if the sample area had been cleared, although this effect was not statistically significant. Ploughing and tree killing are variable depending on land type, but the former has affected about 40% of the Acacia on clay land type, effectively eliminating options for natural regrowth. The proportion of decade-site combinations that were reported as having no fires increased from 22% in the 1950s to an average of 42% for subsequent decades, although the reporting of more than one fire per decade has been relatively constant through the study period. The reporting of at least one fire per decade varies from 46% for the Acacia on sand land type to 77% for the Eucalypt on sand land type for decade-site combinations. Fires are more intense when associated with clearing than in uncleared vegetation, but the proportion of cool and hot fires is relatively constant between land types in uncleared vegetation. Nearly

Mapping landscape phenology preference of yellow-billed cuckoo with AVHRR data

USGS Publications Warehouse

Wallace, Cynthia S.A.; Villarreal, Miguel; van Riper, Charles

2013-01-01

We mapped habitat for threatened Yellow-billed Cuckoo (Coccycus americanus occidentalis) in the State of Arizona using the temporal greenness dynamics of the landscape, or the landscape phenology. Landscape phenometrics were derived from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) data for 1998 and 1999 by using Fourier harmonic analysis to analyze the waveform of the annual NDVI profile at each pixel. We modeled the spatial distribution of Yellow-billed Cuckoo habitat by coupling the field data of Cuckoo presence or absence and point-based samples of riparian and cottonwood-willow vegetation types with satellite phenometrics for 1998. Models were validated using field and satellite data collected in 1999. The results indicate that Yellow-billed Cuckoo occupy locations within their preferred habitat that exhibit peak greenness after the start of the summer monsoon and are greener and more dynamic than “average” habitat. Identification of preferred phenotypes within recognized habitat areas can be used to refine habitat models, inform predictions of habitat response to climate change, and suggest adaptation strategies.

Variation of microorganism concentrations in urban stormwater runoff with land use and seasons.

PubMed

Selvakumar, Ariamalar; Borst, Michael

2006-03-01

Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential and landscaped commercial). The concentrations of microorganisms in the stormwater runoff were found to be similar in magnitude to, but less variable than, those reported in the stormwater National Pollutant Discharge Elimination System (NPDES) database. Microorganism concentrations from high-density residential areas were higher than those associated with low-density residential and landscaped commercial areas. Since the outfalls were free of sanitary wastewater cross-connections, the major sources of microorganisms to the stormwater runoff were most likely from the feces of domestic animals and wildlife. Concentrations of microorganisms were significantly affected by the season during which the samples were collected. The lowest concentrations were observed during winter except for Staphylococcus aureus. The Pearson correlation coefficients among different indicators showed weak linear relationships and the relationships were statistically significant. However, the relationships between indicators and pathogens were poorly correlated and were not statistically significant, suggesting the use of indicators as evidence of the presence of pathogens is not appropriate. Further, the correlation between the concentration of the traditionally monitored indicators (total coliforms and fecal coliforms) and the suggested substitutes (enterococci and E. coli) is weak, but statistically significant, suggesting that historical time series will be only a qualitative indicator of impaired waters under the revised criteria for recreational water quality by the US EPA.

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

NASA Astrophysics Data System (ADS)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA

Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

2010-01-01

Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

Trends in land surface phenology and atmospheric CO2 seasonality in the Northern Hemisphere terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Gonsamo, A.; Chen, J. M.

2017-12-01

Northern terrestrial ecosystems have shown global warming-induced advances in start, delays in end, and thus increased lengths of growing season and gross photosynthesis in recent decades. The tradeoffs between seasonal dynamics of two opposing fluxes, CO2 uptake through photosynthesis and release through respiration, determine the influence of the terrestrial ecosystems on the atmospheric CO2 concentration and 13C/12C isotope ratio seasonality. Atmospheric CO2 and 13C/12C seasonality is controlled by vegetation phenology, but is not identical because growth will typically commence some time before and terminate some time after the net carbon exchange changes sign in spring and autumn, respectively. Here, we use 34-year satellite normalized difference vegetation index (NDVI) observations to determine how changes in vegetation productivity and phenology affect both the atmospheric CO2 and 13C/12C seasonality. Differences and similarities in recent trends of CO2 and 13C/12C seasonality and vegetation phenology will be discussed. Furthermore, we use the NDVI observations, and atmospheric CO2 and 13C/12C data to show the trends and variability of the timing of peak season plant activity. Preliminary results show that the peak season plant activity of the Northern Hemisphere extra-tropical terrestrial ecosystems is shifting towards spring, largely in response to the warming-induced advance of the start of growing season. Besides, the spring-ward shift of the peak plant activity is contributing the most to the increasing peak season productivity. In other words, earlier start of growing season is highly linked to earlier arrival of peak of season and higher NDVI. Changes in the timing of peak season plant activity are expected to disrupt the synchrony of biotic interaction and exert strong biophysical feedbacks on climate by modifying the surface albedo and energy budget.

Dynamic integration of land use changes in a hydrologic assessment of a rapidly developing Indian catchment.

PubMed

Wagner, Paul D; Bhallamudi, S Murty; Narasimhan, Balaji; Kantakumar, Lakshmi N; Sudheer, K P; Kumar, Shamita; Schneider, Karl; Fiener, Peter

2016-01-01

Rapid land use and land-cover changes strongly affect water resources. Particularly in regions that experience seasonal water scarcity, land use scenario assessments provide a valuable basis for the evaluation of possible future water shortages. The objective of this study is to dynamically integrate land use model projections with a hydrologic model to analyze potential future impacts of land use change on the water resources of a rapidly developing catchment upstream of Pune, India. For the first time projections from the urban growth and land use change model SLEUTH are employed as a dynamic input to the hydrologic model SWAT. By this means, impacts of land use changes on the water balance components are assessed for the near future (2009-2028) employing four different climate conditions (baseline, IPCC A1B, dry, wet). The land use change modeling results in an increase of urban area by +23.1% at the fringes of Pune and by +12.2% in the upper catchment, whereas agricultural land (-14.0% and -0.3%, respectively) and semi-natural area (-9.1% and -11.9%, respectively) decrease between 2009 and 2028. Under baseline climate conditions, these land use changes induce seasonal changes in the water balance components. Water yield particularly increases at the onset of monsoon (up to +11.0mm per month) due to increased impervious area, whereas evapotranspiration decreases in the dry season (up to -15.1mm per month) as a result of the loss of irrigated agricultural area. As the projections are made for the near future (2009-2028) land use change impacts are similar under IPCC A1B climate conditions. Only if more extreme dry years occur, an exacerbation of the land use change impacts can be expected. Particularly in rapidly changing environments an implementation of both dynamic land use change and climate change seems favorable to assess seasonal and gradual changes in the water balance. Copyright © 2015 Elsevier B.V. All rights reserved.

Explaining variations in the diversity of parasitoid assemblages in a biosphere reserve of Mexico: evidence from vegetation, land management and seasonality.

PubMed

González-Moreno, A; Bordera, S; Leirana-Alcocer, J; Delfín-González, H; Ballina-Gómez, H S

2017-11-23

Insect fauna biodiversity in natural protected areas has not been thoroughly studied. Therefore, the aim of this work was to assess whether and how vegetation types, land management and seasonality influence the diversity of Ichneumonidae (Hymenoptera) in the Ría Lagartos Biosphere Reserve (Mexico). A sampling programme was conducted using Malaise traps from 2008 to 2009 in three vegetation types, each with two conservation zones (core and buffer zones). Three seasons were considered: rainy, dry and north-winds (isolated storms from November to February). A total of 336 species were identified. Rarefaction and Generalized Linear Model indicated higher species richness and abundance, respectively, in the buffer zone of the dry forest; possible explanations for this finding include the intermediate disturbance hypothesis, wherein diversity can be higher in sites where disturbance is not very frequent or very intense, and the 'enemies hypothesis', wherein structural complexity and high plant diversity favour increased predators or, in this case, parasitoids. Diversity was higher during the rainy season, which may have been due to the higher availability of resources. Vegetation and management had a positive impact on the Coc (attack cocoons and pupae) and Myc (attack concealed larvae living in the fruiting bodies of mushrooms) parasitoid guilds. Members of the Coc guild are generalist parasitoids, which may be favoured in complex vegetation with a high richness of potential hosts and non-hosts. The Myc guild requires certain environmental conditions that promote fungal growth, such as humidity, that is absent in the other vegetation types of savannah and coastal dune scrubland.

Analysis of seasonal characteristics of Sambhar Salt Lake, India, from digitized Space Shuttle photography

NASA Technical Reports Server (NTRS)

Lulla, Kamlesh P.; Helfert, Michael R.

1989-01-01

Sambhar Salt Lake is the largest salt lake (230 sq km) in India, situated in the northwest near Jaipur. Analysis of Space Shuttle photographs of this ephemeral lake reveals that water levels and lake basin land-use information can be extracted by both the digital and manual analysis techniques. Seasonal characteristics captured by the two Shuttle photos used in this study show that additional land use/cover categories can be mapped from the dry season photos. This additional information is essential for precise cartographic updates, and provides seasonal hydrologic profiles and inputs for potential mesoscale climate modeling. This paper extends the digitization and mensuration techniques originally developed for space photography and applied to other regions (e.g., Lake Chad, Africa, and Great Salt Lake, USA).

Response of Amazon Fires to the 2015/2016 El Niño and Evaluation of a Seasonal Fire Season Severity Forecast

NASA Astrophysics Data System (ADS)

Randerson, J. T.

2016-12-01

Recent work has established that year-to-year variability in drought and fire within the Amazon responds to a dual forcing from ocean-atmosphere interactions in the tropical Pacific and North Atlantic. Teleconnections between the Pacific and the Amazon are strongest between October and March, when El Niño contributes to below-average precipitation during the wet season. A reduced build-up of soil moisture during the wet season, in turn, may limit water availability and transpiration in tropical forests during the following dry season, lowering surface humidity, drying fuels, and allowing fires to spread more easily through the understory. The delayed influence of soil moisture through this land - atmosphere coupling provides a means to predict fire season severity 3-6 months before the onset of the dry season. With the aim of creating new opportunities for forest conservation, we have developed an experimental seasonal fire forecasting system for the Amazon. The 2016 fire season severity forecast, released in June by UCI and NASA, predicts unusually high risk across eastern Peru, northern Bolivia, and Brazil. Several surface and satellite data streams confirm that El Niño teleconnections had a significant impact on wet season hydrology within the Amazon. Rainfall observations from the Global Precipitation Climatology Centre provided evidence that cumulative precipitation deficits during August-April were 1 to 2 standard deviations below the long-term mean for most of the basin. These observations were corroborated by strong negative terrestrial water storage anomalies measured by the Gravity Recovery and Climate Experiment, and by fluorescence and vegetation index observations from other sensors that indicated elevated canopy stress. By August 3rd, satellite observations showed above average fire activity in most, but not all, forecast regions. Using additional satellite observations that become available later this year, we plan to describe the full spatial and

Watershed and land use-based sources of trace metals in urban storm water.

PubMed

Tiefenthaler, Liesl L; Stein, Eric D; Schiff, Kenneth C

2008-02-01

Trace metal contributions in urban storm water are of concern to environmental managers because of their potential impacts on ambient receiving waters. The mechanisms and processes that influence temporal and spatial patterns of trace metal loading in urban storm water, however, are not well understood. The goals of the present study were to quantify trace metal event mean concentration (EMC), flux, and mass loading associated with storm water runoff from representative land uses; to compare EMC, flux, and mass loading associated with storm water runoff from urban (developed) and nonurban (undeveloped) watersheds; and to investigate within-storm and within-season factors that affect trace metal concentration and flux. To achieve these goals, trace metal concentrations were measured in 315 samples over 11 storm events in five southern California, USA, watersheds representing eight different land use types during the 2000 through 2005 storm seasons. In addition, 377 runoff samples were collected from 12 mass emission sites (end of watershed) during 15 different storm events. Mean flux at land use sites ranged from 24 to 1,238, 0.1 to 1,272, and 6 to 33,189 g/km(2) for total copper, total lead, and total zinc, respectively. Storm water runoff from industrial land use sites contained higher EMCs and generated greater flux of trace metals than other land use types. For all storms sampled, the highest metal concentrations occurred during the early phases of storm water runoff, with peak concentrations usually preceding peak flow. Early season storms produced significantly higher metal flux compared with late season storms at both mass emission and land use sites.

Discrimination And Biophysical Characterization Of Brazilian Cerrado Physiognomies With Eo-1 Hyperspectral Hyperion

NASA Technical Reports Server (NTRS)

Miura, Tomoaki; Huete, Alfredo R.; Ferreira, Laerte G.; Sano, Edson E.

2004-01-01

The savanna, typically found in the sub-tropics and seasonal tropics, are the dominant vegetation biome type in the southern hemisphere, covering approximately 45% of the South America. In Brazil, the savanna, locally known as "cerrado," is the most intensely stressed biome with both natural environmental pressures (e.g., the strong seasonality in weather, extreme soil nutrient impoverishment, and widespread fire occurrences) and rapid/aggressive land conversions (Skole et al., 1994; Ratter et al., 1997). Better characterization and discrimination of cerrado physiognomies are needed in order to improve understanding of cerrado dynamics and its impact on carbon storage, nutrient dynamics, and the prospect for sustainable land use in the Brazilian cerrado biome. Satellite remote sensing have been known to be a useful tool for land cover and land use mapping (Rougharden et al., 1991; Hansen et al., 2000). However, attempts to discriminate and classify Brazilian cerrado using multi-spectral sensors (e.g., Landsat TM) and/or moderate resolution sensors (e.g., NOAA AVHRR NDVI) have often resulted in a limited success due partly to small contrasts depicted in their multiband, spectral reflectance or vegetation index values among cerrado classes (Seyler et al., 2002; Fran a and Setzer, 1998). In this study, we aimed to improve discrimination as well as biophysical characterization of the Brazilian cerrado physiognomies with hyperspectral remote sensing. We used Hyperion, the first satellite-based hyperspectral imager, onboard the Earth Observing-1 (EO-1) platform.

Seasonal Extratropical Storm Activity Potential Predictability and its Origins during the Cold Seasons

NASA Astrophysics Data System (ADS)

Pingree-Shippee, K. A.; Zwiers, F. W.; Atkinson, D. E.

2016-12-01

Extratropical cyclones (ETCs) often produce extreme hazardous weather conditions, such as high winds, blizzard conditions, heavy precipitation, and flooding, all of which can have detrimental socio-economic impacts. The North American east and west coastal regions are both strongly influenced by ETCs and, subsequently, land-based, coastal, and maritime economic sectors in Canada and the USA all experience strong adverse impacts from extratropical storm activity from time to time. Society would benefit if risks associated with ETCs and storm activity variability could be reliably predicted for the upcoming season. Skillful prediction would enable affected sectors to better anticipate, prepare for, manage, and respond to storm activity variability and the associated risks and impacts. In this study, the potential predictability of seasonal variations in extratropical storm activity is investigated using analysis of variance to provide quantitative and geographical observational evidence indicative of whether it may be possible to predict storm activity on the seasonal timescale. This investigation will also identify origins of the potential predictability using composite analysis and large-scale teleconnections (Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation), providing the basis upon which seasonal predictions can be developed. Seasonal potential predictability and its origins are investigated for the cold seasons (OND, NDJ, DJF, JFM) during the 1979-2015 time period using daily mean sea level pressure, absolute pressure tendency, and 10-m wind speed from the ECMWF ERA-Interim reanalysis as proxies for extratropical storm activity. Results indicate potential predictability of seasonal variations in storm activity in areas strongly influenced by ETCs and with origins in the investigated teleconnections. For instance, the North Pacific storm track has considerable potential predictability and with notable origins in the SO and PDO.

Satellite view of seasonal greenness trends and controls in South Asia

NASA Astrophysics Data System (ADS)

Sarmah, Sangeeta; Jia, Gensuo; Zhang, Anzhi

2018-03-01

South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982–2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

Land surface phenology and land surface temperature changes along an urban-rural gradient in Yangtze River Delta, china.

PubMed

Han, Guifeng; Xu, Jianhua

2013-07-01

Using SPOT/VGT NDVI time series images (2002-2009) and MODIS/LST images (2002-2009) smoothed by a Savitzky-Golay filter, the land surface phenology (LSP) and land surface temperature (LST), respectively, are extracted for six cities in the Yangtze River Delta, China, including Shanghai, Hangzhou, Nanjing, Changzhou, Wuxi, and Suzhou. The trends of the averaged LSP and LST are analyzed, and the relationship between these values is revealed along the urban-rural gradient. The results show that urbanization advances the start of the growing season, postpones the end of the growing season, prolongs the growing season length (GSL), and reduces the difference between maximal NDVI and minimal NDVI in a year (NDVIamp). More obvious changes occur in surface vegetation phenology as the urbanized area is approached. The LST drops monotonously and logarithmically along the urban-rural gradient. Urbanization generally affects the LSP of the surrounding vegetation within 6 km to the urban edge. Except for GSL, the difference in the LSP between urban and rural areas has a significant logarithmic relationship with the distance to the urban edge. In addition, there is a very strong linear relationship between the LSP and the LST along the urban-rural gradient, especially within 6 km to the urban edge. The correlations between LSP and gross domestic product and population density reveal that human activities have considerable influence on the land surface vegetation growth.

Seasonal and Geographical Variation of Dengue Vectors in Narathiwat, South Thailand

PubMed Central

Boonklong, Ornanong; Bhumiratana, Adisak

2016-01-01

Using GIS-based land use map for the urban-rural division (the relative ratio of population density adjusted to relatively Aedes-infested land area), we demonstrated significant independent observations of seasonal and geographical variation of Aedes aegypti and Aedes albopictus vectors between Muang Narathiwat district (urban setting) and neighbor districts (rural setting) of Narathiwat, Southern Thailand, based on binomial distribution of Aedes vectors in water-holding containers (water storage containers, discarded receptacles, miscellaneous containers, and natural containers). The distribution of Aedes vectors was influenced seasonally by breeding outdoors rather than indoors in all 4 containers. Accordingly, both urban and rural settings elicited significantly seasonal (wet versus dry) distributions of Ae. aegypti larvae observed in water storage containers (P = 0.001 and P = 0.002) and natural containers (P = 0.016 and P = 0.015), whereas, in rural setting, the significant difference was observed in discarded receptacles (P = 0.028) and miscellaneous containers (P < 0.001). Seasonal distribution of Ae. albopictus larvae in any containers in urban setting was not remarkably noticed, whereas, in rural setting, the significant difference was observed in water storage containers (P = 0.007) and discarded receptacles (P < 0.001). Moreover, the distributions of percentages of container index for Aedes-infested households in dry season were significantly lower than that in other wet seasons, P = 0.034 for urban setting and P = 0.001 for rural setting. Findings suggest that seasonal and geographical variation of Aedes vectors affect the infestation in those containers in human inhabitations and surroundings. PMID:27437001

Land use affects the net ecosystem CO2 exchange and its components in mountain grasslands

PubMed Central

Schmitt, M.; Bahn, M.; Wohlfahrt, G.; Tappeiner, U.; Cernusca, A.

2011-01-01

Changes in land use and management have been strongly affecting mountain grassland, however, their effects on the net ecosystem exchange of CO2 (NEE) and its components have not yet been well documented. We analysed chamber-based estimates of NEE, gross primary productivity (GPP), ecosystem respiration (R) and light use efficiency (LUE) of six mountain grasslands differing in land use and management, and thus site fertility, for the growing seasons of 2002 to 2008. The main findings of the study are that: (1) land use and management affected seasonal NEE, GPP and R, which all decreased from managed to unmanaged grasslands; (2) these changes were explained by differences in leaf area index (LAI), biomass and leaf-area-independent changes that were likely related to photosynthetic physiology; (3) diurnal variations of NEE were primarily controlled by photosynthetically active photon flux density and soil and air temperature; seasonal variations were associated with changes in LAI; (4) parameters of light response curves were generally closely related to each other, and the ratio of R at a reference temperature/ maximum GPP was nearly constant across the sites; (5) similarly to our study, maximum GPP and R for other grasslands on the globe decreased with decreasing land use intensity, while their ratio remained remarkably constant. We conclude that decreasing intensity of management and, in particular, abandonment of mountain grassland lead to a decrease in NEE and its component processes. While GPP and R are generally closely coupled during most of the growing season, GPP is more immediately and strongly affected by land management (mowing, grazing) and season. This suggests that management and growing season length, as well as their possible future changes, may play an important role for the annual C balance of mountain grassland. PMID:23293657

Tracking Fallow Land in California Using USDA's Cropland Data Layer

NASA Astrophysics Data System (ADS)

Zakzeski, A.; mueller, R.; Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P.; Jones, J.

2013-12-01

The agricultural landscape of California has become the focus of a new research project combining the efforts of the US Department of Agriculture (USDA) National Agricultural Statistics Service (NASS), the US Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA). The project's goal is to provide quantitative early and in season estimates derived from satellite data on the fallow/idle agricultural land throughout the State of California since water resources have become so constrained due to inadequate amounts of precipitation and high temperatures. As part of the research effort NASS has agreed to accelerate their established remote sensing program known as the Cropland Data Layer (CDL) in order to produce an idle mask derived over California as early as June with continued iterations throughout the growing season through October. The Cropland Data Layer is a land cover classification product produced by combining up to date, field level farm data from the Farm Service Agency's (FSA) 578 survey with a collection of satellite data over the growing season from both the Disaster Monitoring Constellation (DMC) and the newly launched Landsat-8 satellite. The combination of ground data and satellite data is used to derive a complex decision tree defining the phenological profiles of each type of agricultural land cover, including fallow and idle, throughout the state. Each CDL categorizes over a hundred types of land cover however for this project NASS creates a binary mask focusing solely on fallow/idle land cover. Each month NASS receives updates on field level farm data from FSA and collects more satellite imagery therefore the accuracies of the CDL and the subsequent idle masks used in this project continually improve as the season progresses. These fallow/idle masks will be made available to the public in the future for other research efforts. Each monthly iteration of the 30 meter CDL and subsequent fallow mask over California

Crop Frequency Mapping for Land Use Intensity Estimation During Three Decades

NASA Astrophysics Data System (ADS)

Schmidt, Michael; Tindall, Dan

2016-08-01

Crop extent and frequency maps are an important input to inform the debate around land value and competitive land uses, food security and sustainability of agricultural practices. Such spatial datasets are likely to support decisions on natural resource management, planning and policy. The complete Landsat Time Series (LTS) archive for 23 Landsat footprints in western Queensland from 1987 to 2015 was used in a multi-temporal mapping approach. Spatial, spectral and temporal information were combined in multiple crop-modelling steps, supported by on ground training data sampled across space and time for the classes Crop and No-Crop. Temporal information within summer and winter growing seasons for each year were summarised, and combined with various vegetation indices and band ratios computed from a mid-season spectral-composite image. All available temporal information was spatially aggregated to the scale of image segments in the mid- season composite for each growing season and used to train a random forest classifier for a Crop and No- Crop classification. Validation revealed that the predictive accuracy varied by growing season and region to be within k = 0.88 to 0.97 and are thus suitable for mapping current and historic cropping activity. Crop frequency maps were produced for all regions at different time intervals. The crop frequency maps were validated separately with a historic crop information time series. Different land use intensities and conversions e.g. from agricultural to pastures are apparent and potential drivers of these conversions are discussed.

Multi-Season Regional Analysis of Multi-Species Occupancy: Implications for Bird Conservation in Agricultural Lands in East-Central Argentina

PubMed Central

Goijman, Andrea Paula; Conroy, Michael. J.; Bernardos, Jaime Nicolás; Zaccagnini, María Elena

2015-01-01

Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow us to continue to

Urban green land cover changes and their relation to climatic variables in an anthropogenically impacted area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Dida, Adrian I.

2017-10-01

Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.

Study to assess the importance of errors introduced by applying NOAA 6 and NOAA 7 AVHRR data as an estimator of vegetative vigor: Feasibility study of data normalization

NASA Technical Reports Server (NTRS)

Duggin, M. J. (Principal Investigator); Piwinski, D.

1982-01-01

The use of NOAA AVHRR data to map and monitor vegetation types and conditions in near real-time can be enhanced by using a portion of each GAC image that is larger than the central 25% now considered. Enlargement of the cloud free image data set can permit development of a series of algorithms for correcting imagery for ground reflectance and for atmospheric scattering anisotropy within certain accuracy limits. Empirical correction algorithms used to normalize digital radiance or VIN data must contain factors for growth stage and for instrument spectral response. While it is not possible to correct for random fluctuations in target radiance, it is possible to estimate the necessary radiance difference between targets in order to provide target discrimination and quantification within predetermined limits of accuracy. A major difficulty lies in the lack of documentation of preprocessing algorithms used on AVHRR digital data.

A warm-season comparison of WRF coupled to the CLM4.0, Noah-MP, and Bucket hydrology land surface schemes over the central USA

NASA Astrophysics Data System (ADS)

Van Den Broeke, Matthew S.; Kalin, Andrew; Alavez, Jose Abraham Torres; Oglesby, Robert; Hu, Qi

2017-11-01

In climate modeling studies, there is a need to choose a suitable land surface model (LSM) while adhering to available resources. In this study, the viability of three LSM options (Community Land Model version 4.0 [CLM4.0], Noah-MP, and the five-layer thermal diffusion [Bucket] scheme) in the Weather Research and Forecasting model version 3.6 (WRF3.6) was examined for the warm season in a domain centered on the central USA. Model output was compared to Parameter-elevation Relationships on Independent Slopes Model (PRISM) data, a gridded observational dataset including mean monthly temperature and total monthly precipitation. Model output temperature, precipitation, latent heat (LH) flux, sensible heat (SH) flux, and soil water content (SWC) were compared to observations from sites in the Central and Southern Great Plains region. An overall warm bias was found in CLM4.0 and Noah-MP, with a cool bias of larger magnitude in the Bucket model. These three LSMs produced similar patterns of wet and dry biases. Model output of SWC and LH/SH fluxes were compared to observations, and did not show a consistent bias. Both sophisticated LSMs appear to be viable options for simulating the effects of land use change in the central USA.

Pre- and Post-Columbian Land Cover Changes and Associated Climate Impacts

NASA Astrophysics Data System (ADS)

Cook, B. I.; Puma, M. J.; Kaplan, J. O.; Anchukaitis, K. J.

2011-12-01

Central America experienced extensive expansion of agricultural land during development of the major Central American societies, followed by widespread abandonment and regrowth of natural vegetation after the European conquest. Here we use a high resolution climate model, in combination with a new land cover reconstruction, to investigate the impact of pre- (1490 C.E.) and post- (1650 C.E.) Columbian land cover change on climate in this region. Pre-Columbian land cover causes significant precipitation reductions over coastal Mexico, the Yucatan, and southern Mexico during the wet season, as replacement of forests with agricultural land reduces evapotranspiration fluxes to the atmosphere. Conversely, precipitation over the Yucatan increases during the dry season, as increased surface warming moves additional moisture into this region from the surrounding oceans. With the post-Columbian period, during which major population declines led to large scale agricultural abandonment, the forest recovery results in a partial, though not complete, return to wetter conditions. Our study finds support for previous work speculating that land cover change associated with the Mayan civilizations may have amplified major droughts in the region, and points to the possibility of a direct biogeophysical response to the forest recovery following the arrival of Europeans.

The effect of anthropogenic emissions corrections on the seasonal cycle of atmospheric CO2

NASA Astrophysics Data System (ADS)

Brooks, B. J.; Hoffman, F. M.; Mills, R. T.; Erickson, D. J.; Blasing, T. J.

2009-12-01

A previous study (Erickson et al. 2008) approximated the monthly global emission estimates of anthropogenic CO2 by applying a 2-harmonic Fourier expansion with coefficients as a function of latitude to annual CO2 flux estimates derived from United States data (Blasing et al. 2005) that were extrapolated globally. These monthly anthropogenic CO2 flux estimates were used to model atmospheric concentrations using the NASA GEOS-4 data assimilation system. Local variability in the amplitude of the simulated CO2 seasonal cycle were found to be on the order of 2-6 ppmv. Here we used the same Fourier expansion to seasonally adjust the global annual fossil fuel CO2 emissions from the SRES A2 scenario. For a total of four simulations, both the annual and seasonalized fluxes were advected in two configurations of the NCAR Community Atmosphere Model (CAM) used in the Carbon-Land Model Intercomparison Project (C-LAMP). One configuration used the NCAR Community Land Model (CLM) coupled with the CASA‧ (carbon only) biogeochemistry model and the other used CLM coupled with the CN (coupled carbon and nitrogen cycles) biogeochemistry model. All four simulations were forced with observed sea surface temperatures and sea ice concentrations from the Hadley Centre and a prescribed transient atmospheric CO2 concentration for the radiation and land forcing over the 20th century. The model results exhibit differences in the seasonal cycle of CO2 between the seasonally corrected and uncorrected simulations. Moreover, because of differing energy and water feedbacks between the atmosphere model and the two land biogeochemistry models, features of the CO2 seasonal cycle were different between these two model configurations. This study reinforces previous findings that suggest that regional near-surface atmospheric CO2 concentrations depend strongly on the natural sources and sinks of CO2, but also on the strength of local anthropogenic CO2 emissions and geographic position. This work further

Response of Arctic Snow and Sea Ice Extents to Melt Season Atmospheric Forcing Across the Land-Ocean Boundary

NASA Astrophysics Data System (ADS)

Bliss, A. C.; Anderson, M. R.

2011-12-01

Little research has gone into studying the concurrent variations in the annual loss of continental snow cover and sea ice extent across the land-ocean boundary, however, the analysis of these data averaged spatially over three study regions located in North America and Eastern and Western Russia, reveals a distinct difference in the response of anomalous snow and sea ice conditions to the atmospheric forcing. This study compares the monthly continental snow cover and sea ice extent loss in the Arctic, during the melt season months (May-August) for the period 1979-2007, with regional atmospheric conditions known to influence summer melt including: mean sea level pressures, 925 hPa air temperatures, and mean 2 m U and V wind vectors from NCEP/DOE Reanalysis 2. The monthly hemispheric snow cover extent data used are from the Rutgers University Global Snow Lab and sea ice extents for this study are derived from the monthly passive microwave satellite Bootstrap algorithm sea ice concentrations available from the National Snow and Ice Data Center. Three case study years (1985, 1996, and 2007) are used to compare the direct response of monthly anomalous sea ice and snow cover areal extents to monthly mean atmospheric forcing averaged spatially over the extent of each study region. This comparison is then expanded for all summer months over the 29 year study period where the monthly persistence of sea ice and snow cover extent anomalies and changes in the sea ice and snow conditions under differing atmospheric conditions are explored further. The monthly anomalous atmospheric conditions are classified into four categories including: warmer temperatures with higher pressures, warmer temperatures with lower pressures, cooler temperatures with higher pressures, and cooler temperatures with lower pressures. Analysis of the atmospheric conditions surrounding anomalous loss of snow and ice cover over the independent study regions indicates that conditions of warmer temperatures

Land surface phenological responses to land use and climate variation in a changing Central Asia

NASA Astrophysics Data System (ADS)

Kariyeva, Jahan

During the last few decades Central Asia has experienced widespread changes in land cover and land use following the socio-economic and institutional transformations of the region catalyzed by the USSR collapse in 1991. The decade-long drought events and steadily increasing temperature regimes in the region came on top of these institutional transformations, affecting the long term and landscape scale vegetation responses. This research is based on the need to better understand the potential ecological and policy implications of climate variation and land use practices in the contexts of landscape-scale changes dynamics and variability patterns of land surface phenology responses in Central Asia. The land surface phenology responses -- the spatio-temporal dynamics of terrestrial vegetation derived from the remotely sensed data -- provide measurements linked to the timing of vegetation growth cycles (e.g., start of growing season) and total vegetation productivity over the growing season, which are used as a proxy for the assessment of effects of variations in environmental settings. Local and regional scale assessment of the before and after the USSR collapse vegetation response patterns in the natural and agricultural systems of the Central Asian drylands was conducted to characterize newly emerging links (since 1991) between coupled human and natural systems, e.g., socio-economic and policy drivers of altered land and water use and distribution patterns. Spatio-temporal patterns of bioclimatic responses were examined to determine how phenology is associated with temperature and precipitation in different land use types, including rainfed and irrigated agricultural types. Phenological models were developed to examine relationship between environmental drivers and effect of their altitudinal and latitudinal gradients on the broad-scale vegetation response patterns in non-cropland ecosystems of the desert, steppe, and mountainous regional landscapes of Central Asia

A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer; Livingston, Gerry P.; Gore, Warren J. (Technical Monitor)

1998-01-01

The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

Diurnal and Seasonal Cold Lands Signatures in SSM/I-scale Microwave Radiometry of the North Slope of Alaska

NASA Technical Reports Server (NTRS)

Kim, Edward J.; England, Anthony W.; Hildebrand, Peter H. (Technical Monitor)

2001-01-01

In this paper, we explore scaling and data assimilation-related issues associated with utilizing passive microwave satellite observations of Cold Lands-in this case, the climatologically and ecologically sensitive arctic tundra. Our approach expands on our earlier work using a one-year dataset from the Radiobrightness Energy Balance Experiment-3 (REBEX-3). REBEX-3 featured a tower-based SSM/I (Special Sensor Microwave/Imager) simulator deployed on the North Slope of Alaska in 1994-95. Two findings are significant here. First, a comparison of tower and satellite signatures at 19 and 37 GHz strongly suggested that the North Slope is radiometrically homogeneous for spatial scales up to SSM/I footprints (approximately 25 km), an unusual and valuable characteristic for monitoring and retrieving land surface conditions. And second, at the plot scale, signatures of snow/no-snow and freeze/thaw transitions were identifiable for tussock tundra land cover, so that even snow-free frozen tundra could be unambiguously distinguished from tundra covered with dry snow, another unusual and valuable characteristic. We present results from analyzing satellite brightness signatures of selected North Slope pixels corresponding to instrumented sites along a transect from the Brooks Range to the Arctic Ocean. A custom EASE (Equal Area Scalable Earth)-Grid processor was used to extract SSMJI data for every orbit with observations of this region during the 1994-95 year. The resulting high temporal-resolution (4-8 points/day), gridded data were then analyzed for evidence of the same diurnal and seasonal signatures seen at the plot scale (through micrometeorological and/or brightness data). Differences between satellite and tower brightness observations are quantified for various conditions at the REBEX-3 site. Such differences from the less-frequent and/or larger-scale satellite observations represent a form of input 'noise' in data assimilation applications. For the other sites, the

Land Cover and Hydrologic Variability in Residential Watersheds: Drivers of N Loss in Sacramento CA

NASA Astrophysics Data System (ADS)

McConaghie, J. B.; Zhou, W.; Cadenasso, M. L.

2011-12-01

A key aspect to understanding N loss from urban systems is the link between landscape heterogeneity and variability in non-point source (NPS) nitrogen (N) flux. Because water transports N across the landscape and into receiving streams as runoff, understanding how landscape heterogeneity influences water quantity and movement is also needed. High variability in N loss has been documented from urban systems. However, typical NPS studies characterize landscape heterogeneity by land use and only weakly explain variability in stream N. Focusing on land cover, rather than land use, may better explain observed variability in N loss because land cover elements may better indicate major drivers of N loss. Also, most studies have been conducted in temperate urban systems with stream flow year round. In semi-arid urban systems, storm flow accounts for the majority of stream discharges, and residential irrigation contributes significantly to flows in the dry season. To address how landscape heterogeneity affects variability in water quantity and quality in urban streams, we examined how land cover influences stream flows and N loss in residential streams of metropolitan Sacramento, CA. We analyzed fine-scale variation in land cover and stream N during base flow and storm events in 4 residential watersheds which differ substantially in land cover. We classified land cover using HERCULES (High Ecological Resolution Classification for Urban Landscapes and Environmental Systems) which was developed specifically for urban systems. HERCULES classifies high-resolution aerial photographs into 5 elements: buildings, pavement, herbaceous and woody vegetation, and bare soil. Streams were sampled for discharge, NO3, and Total N using auto samplers during storms in the 2010-2011 rainy season and monthly in the dry season. Partial correlation analysis and multivariate models describe the relationships between land cover elements, water retention, and stream N in these watersheds. We found

Monitoring and modeling agricultural drought for famine early warning (Invited)

NASA Astrophysics Data System (ADS)

Verdin, J. P.; Funk, C.; Budde, M. E.; Lietzow, R.; Senay, G. B.; Smith, R.; Pedreros, D.; Rowland, J.; Artan, G. A.; Husak, G. J.; Michaelsen, J.; Adoum, A.; Galu, G.; Magadzire, T.; Rodriguez, M.

2009-12-01

The Famine Early Warning Systems Network (FEWS NET) makes quantitative estimates of food insecure populations, and identifies the places and periods during which action must be taken to assist them. Subsistence agriculture and pastoralism are the predominant livelihood systems being monitored, and they are especially drought-sensitive. At the same time, conventional climate observation networks in developing countries are often sparse and late in reporting. Consequently, remote sensing has played a significant role since FEWS NET began in 1985. Initially there was heavy reliance on vegetation index imagery from AVHRR to identify anomalies in landscape greenness indicative of drought. In the latter part of the 1990s, satellite rainfall estimates added a second, independent basis for identification of drought. They are used to force crop water balance models for the principal rainfed staple crops in twenty FEWS NET countries. Such models reveal seasonal moisture deficits associated with yield reduction on a spatially continuous basis. In 2002, irrigated crops in southwest Asia became a concern, and prompted the implementation of a gridded energy balance model to simulate the seasonal mountain snow pack, the main source of irrigation water. MODIS land surface temperature data are also applied in these areas to directly estimate actual seasonal evapotranspiration on the irrigated lands. The approach reveals situations of reduced irrigation water supply and crop production due to drought. The availability of MODIS data after 2000 also brought renewed interest in vegetation index imagery. MODIS NDVI data have proven to be of high quality, thanks to significant spectral and spatial resolution improvements over AVHRR. They are vital to producing rapid harvest assessments for drought-impacted countries in Africa and Asia. The global food crisis that emerged in 2008 has led to expansion of FEWS NET monitoring to over 50 additional countries. Unlike previous practice, these

Drought Risk Identification: Early Warning System of Seasonal Agrometeorological Drought

NASA Astrophysics Data System (ADS)

Dalecios, Nicolas; Spyropoulos, Nicos V.; Tarquis, Ana M.

2014-05-01

By considering drought as a hazard, drought types are classified into three categories, namely meteorological or climatological, agrometeorological or agricultural and hydrological drought and as a fourth class the socioeconomic impacts can be considered. This paper addresses agrometeorological drought affecting agriculture within the risk management framework. Risk management consists of risk assessment, as well as a feedback on the adopted risk reduction measures. And risk assessment comprises three distinct steps, namely risk identification, risk estimation and risk evaluation. This paper deals with the quantification and monitoring of agrometeorological drought, which constitute part of risk identification. For the quantitative assessment of agrometeorological or agricultural drought, as well as the computation of spatiotemporal features, one of the most reliable and widely used indices is applied, namely the Vegetation Health Index (VHI). The computation of VHI is based on satellite data of temperature and the Normalized Difference Vegetation Index (NDVI). The spatiotemporal features of drought, which are extracted from VHI are: areal extent, onset and end time, duration and severity. In this paper, a 20-year (1981-2001) time series of NOAA/AVHRR satellite data is used, where monthly images of VHI are extracted. Application is implemented in Thessaly, which is the major agricultural region of Greece characterized by vulnerable and drought-prone agriculture. The results show that every year there is a seasonal agrometeorological drought with a gradual increase in the areal extent and severity with peaks appearing usually during the summer. Drought monitoring is conducted by monthly remotely sensed VHI images. Drought early warning is developed using empirical relationships of severity and areal extent. In particular, two second-order polynomials are fitted, one for low and the other for high severity drought, respectively. The two fitted curves offer a seasonal

Rainforest-initiated wet season onset over the southern Amazon.

PubMed

Wright, Jonathon S; Fu, Rong; Worden, John R; Chakraborty, Sudip; Clinton, Nicholas E; Risi, Camille; Sun, Ying; Yin, Lei

2017-08-08

Although it is well established that transpiration contributes much of the water for rainfall over Amazonia, it remains unclear whether transpiration helps to drive or merely responds to the seasonal cycle of rainfall. Here, we use multiple independent satellite datasets to show that rainforest transpiration enables an increase of shallow convection that moistens and destabilizes the atmosphere during the initial stages of the dry-to-wet season transition. This shallow convection moisture pump (SCMP) preconditions the atmosphere at the regional scale for a rapid increase in rain-bearing deep convection, which in turn drives moisture convergence and wet season onset 2-3 mo before the arrival of the Intertropical Convergence Zone (ITCZ). Aerosols produced by late dry season biomass burning may alter the efficiency of the SCMP. Our results highlight the mechanisms by which interactions among land surface processes, atmospheric convection, and biomass burning may alter the timing of wet season onset and provide a mechanistic framework for understanding how deforestation extends the dry season and enhances regional vulnerability to drought.

Rainforest-initiated wet season onset over the southern Amazon

PubMed Central

Wright, Jonathon S.; Fu, Rong; Worden, John R.; Chakraborty, Sudip; Clinton, Nicholas E.; Risi, Camille; Sun, Ying; Yin, Lei

2017-01-01

Although it is well established that transpiration contributes much of the water for rainfall over Amazonia, it remains unclear whether transpiration helps to drive or merely responds to the seasonal cycle of rainfall. Here, we use multiple independent satellite datasets to show that rainforest transpiration enables an increase of shallow convection that moistens and destabilizes the atmosphere during the initial stages of the dry-to-wet season transition. This shallow convection moisture pump (SCMP) preconditions the atmosphere at the regional scale for a rapid increase in rain-bearing deep convection, which in turn drives moisture convergence and wet season onset 2–3 mo before the arrival of the Intertropical Convergence Zone (ITCZ). Aerosols produced by late dry season biomass burning may alter the efficiency of the SCMP. Our results highlight the mechanisms by which interactions among land surface processes, atmospheric convection, and biomass burning may alter the timing of wet season onset and provide a mechanistic framework for understanding how deforestation extends the dry season and enhances regional vulnerability to drought. PMID:28729375

The correlated k-distribution technique as applied to the AVHRR channels

NASA Technical Reports Server (NTRS)

Kratz, David P.

1995-01-01

Correlated k-distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k-distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k-distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k-distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k-distribution's principal advantages is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Variation and Trends of Landscape Dynamics, Land Surface Phenology and Net Primary Production of the Appalachian Mountains

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

Wang, Yeqiao; Zhao, Jianjun; Zhou, Yuyu

2012-12-15

The gradients of the Appalachian Mountains in elevations and latitudes provide a unique regional perspective of landscape variations in the eastern United States and a section of the southeastern Canada. This study reveals patterns and trends of landscape dynamics, land surface phenology and ecosystem production along the Appalachian Mountains using time series data from Global Inventory Modeling and Mapping Studies (GIMMS) and AVHRR Global Production Efficiency Model (GloPEM) datasets. We analyzed the spatial and temporal patterns of Normalized Difference Vegetation Index (NDVI), length of growing season (LOS) and net primary production (NPP) of selected ecoregions along the Appalachian Mountains regions.more » We compared the results out of the Appalachian Mountains regions in different spatial contexts including the North America and the Appalachian Trail corridor area. To reveal latitudinal variations we analyzed data and compared the results between 30°N-40°N and 40°N-50°N latitudes. The result revealed significant decreases in annual peak NDVI in the Appalachian Mountains regions. The trend for the Appalachian Mountains regions was -0.0018 (R2=0.55, P<0.0001) NDVI unit decrease per year during 25 years between 1982 and 2006. The LOS had prolonged 0.3 day yr-1 during 25 years over the Appalachian Mountains regions. The NPP increased by 2.68 gC m-2yr-2 in Appalachian Mountains regions from 1981 to 2000. The comparison with the North America reveals the effects of topography and ecosystem compositions of the Appalachian Mountains. The comparison with the Appalachian Trail corridor area provides a regional mega-transect view of the measured variables.« less

Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics

NASA Astrophysics Data System (ADS)

Ai, L.; Shi, Z. H.; Yin, W.; Huang, X.

2015-04-01

Landscape characteristics are widely accepted as strongly influencing stream water quality in heterogeneous watersheds. Understanding the relationships between landscape and specific water contaminant can greatly improve the predictability of potential contamination and the assessment of contaminant export. In this work, we examined the combined effects of watershed complexity, in terms of land use and physiography, on specific water contaminant across watersheds close to the Danjiangkou Reservoir. The land use composition, land use pattern, morphometric variables and soil properties were calculated at the watershed scale and considered potential factors of influence. Due to high co-dependence of these watershed characteristics, partial least squares regression was used to elucidate the linkages between some specific water contaminants and the 16 selected watershed characteristic variables. Water contaminant maps revealed spatial and seasonal heterogeneity. The dissolved oxygen values in the dry season were higher than those in the wet season, whereas the other contaminant concentrations displayed the opposite trend. The studied watersheds which are influenced strongly by urbanization, showed higher levels of ammonia nitrogen, total phosphorus, potassium permanganate index and petroleum, and lower levels of dissolved oxygen. The urban land use, largest patch index and the hypsometric integral were the dominant factors affecting specific water contaminant.

An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Casciello, D.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2011-05-01

Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed. In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique) to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006. The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical) and high spatial (radar) resolution satellite systems.

Effect of Land Use, Seasonality, and Hydrometeorological Conditions on the K+ Concentration-Discharge Relationship During Different Types of Floods in Carpathian Foothills Catchments (Poland).

PubMed

Siwek, Joanna P; Żelazny, Mirosław; Siwek, Janusz; Szymański, Wojciech

2017-01-01

The purpose of the study was to determine the role of land use, seasonality, and hydrometeorological conditions on the relationship between stream water potassium (K + ) concentration and discharge during different types of floods-short- and long-duration rainfall floods as well as snowmelt floods on frozen and thawed soils. The research was conducted in small catchments (agricultural, woodland, mixed-use) in the Carpathian Foothills (Poland). In the woodland catchment, lower K + concentrations were noted for each given specific runoff value for summer rainfall floods versus snowmelt floods (seasonal effect). In the agricultural and mixed-use catchments, the opposite was true due to their greater ability to flush K + out of the soil in the summer. In the stream draining woodland catchment, higher K + concentrations occurred during the rising limb than during the falling limb of the hydrograph (clockwise hysteresis) for all flood types, except for snowmelt floods with the ground not frozen. In the agricultural catchment, clockwise hystereses were produced for short- and long-duration rainfall floods caused by high-intensity, high-volume rainfall, while anticlockwise hystereses were produced for short- and long-duration rainfall floods caused by low-intensity, low-volume rainfall as well as during snowmelt floods with the soil frozen and not frozen. In the mixed-use catchment, the hysteresis direction was also affected by different lag times for water reaching stream channels from areas with different land use. K + hystereses for the woodland catchment were more narrow than those for the agricultural and mixed-use catchments due to a smaller pool of K + in the woodland catchment. In all streams, the widest hystereses were produced for rainfall floods preceded by a long period without rainfall.

Land cover mapping of North and Central America—Global Land Cover 2000

USGS Publications Warehouse

Latifovic, Rasim; Zhu, Zhi-Liang

2004-01-01

The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

[Difference of Karst Carbon Sink Under Different Land Use and Land Cover Areas in Dry Season].

PubMed

Zhao, Rui-yi; Liang, Zuo-bing; Wang, Zun-bo; Yu, Zheng-liang; Jiang, Ze-li

2015-05-01

In order to identify the distinction of soil CO2 consumed by carbonate rock dissolution, Baishuwan spring, Lanhuagou spring and Hougou spring were selected as objects to monitor the hydrochemistry from November 2013 to May 2014. The results showed that the highest HCO3- concentration was observed in Baishuwan spring which is covered by pine forest, while the lowest HCO3- concentration was observed in Hougou spring which is mainly covered by cultivated land. In Baishuwan spring, HCO3- was mainly derived from carbonic acid dissolving carbonate rock and the molar ratio between Ca(2+) + Mg2+ and HCO3- was close to 0. 5; while the molar ratio between Ca(2+) + Mg2+ and HCO3- exceeded 0.5 because the carbonate rock in Lanhuagou spring and Hougou spring was mainly dissolved by nitric acid and sulfuric acid. Because of the input of litter and the fact that gas-permeability of soil was limited in Baishuwan spring catchment, most of soil CO2 was dissolved in infiltrated water and reacted with bedrock. However, in Lanhuagou spring catchment and Hougou spring catchment, porous soil made soil CO2 easier to return to the atmosphere in the form of soil respiration. Therefore, in order to accurately estimate karst carbon sink, it was required to clarify the distinction of CO2 consumption by carbonate rock dissolution under different land use and land cover areas.

Environmental controls on seasonal ecosystem evapotranspiration/potential evapotranspiration ratio as determined by the global eddy flux measurements

NASA Astrophysics Data System (ADS)

Liu, Chunwei; Sun, Ge; McNulty, Steven G.; Noormets, Asko; Fang, Yuan

2017-01-01

The evapotranspiration / potential evapotranspiration (AET / PET) ratio is traditionally termed as the crop coefficient (Kc) and has been generally used as ecosystem evaporative stress index. In the current hydrology literature, Kc has been widely used as a parameter to estimate crop water demand by water managers but has not been well examined for other types of ecosystems such as forests and other perennial vegetation. Understanding the seasonal dynamics of this variable for all ecosystems is important for projecting the ecohydrological responses to climate change and accurately quantifying water use at watershed to global scales. This study aimed at deriving monthly Kc for multiple vegetation cover types and understanding its environmental controls by analyzing the accumulated global eddy flux (FLUXNET) data. We examined monthly Kc data for seven vegetation covers, including open shrubland (OS), cropland (CRO), grassland (GRA), deciduous broad leaf forest (DBF), evergreen needle leaf forest (ENF), evergreen broad leaf forest (EBF), and mixed forest (MF), across 81 sites. We found that, except for evergreen forests (EBF and ENF), Kc values had large seasonal variation across all land covers. The spatial variability of Kc was well explained by latitude, suggesting site factors are a major control on Kc. Seasonally, Kc increased significantly with precipitation in the summer months, except in EBF. Moreover, leaf area index (LAI) significantly influenced monthly Kc in all land covers, except in EBF. During the peak growing season, forests had the highest Kc values, while croplands (CRO) had the lowest. We developed a series of multivariate linear monthly regression models for Kc by land cover type and season using LAI, site latitude, and monthly precipitation as independent variables. The Kc models are useful for understanding water stress in different ecosystems under climate change and variability as well as for estimating seasonal ET for large areas with mixed

Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers

NASA Astrophysics Data System (ADS)

Poveda, Germán.; Jaramillo, Liliana; Vallejo, Luisa F.

2014-01-01

We study the seasonal dynamics of the eastern Pacific (CHOCO) and Caribbean low-level jets (LLJ), and aerial rivers (AR) acting on tropical and subtropical South America. Using the ERA-Interim reanalysis (1979-2012), we show that the convergence of both LLJs over the eastern Pacific-western Colombia contributes to the explanation of the region's world-record rainfall. Diverse variables involved in the transport and storage of moisture permit the identification of an AR over northern South America involving a midtropospheric easterly jet that connects the Atlantic and Pacific Oceans across the Andes, with stronger activity in April to August. Other major seasonal AR pathways constitute part of a large gyre originating over the tropical North Atlantic, veering to the southeast over the eastern Andes and reaching regions of northern Argentina and southeastern Brazil. We illustrate the distribution of average seasonal precipitation along the LLJs and AR pathways with data from the Tropical Rainfall Measuring Mission (1998-2011), combined with considerations of CAPE, topography, and land cover. In addition, the theory of the biotic pump of atmospheric moisture (BiPAM) is tested at seasonal time scales, and found to hold in 8 out of 12 ARs, and 22 out of 32 forest-covered tracks (64% in distance) along the ARs. Deviations from BiPAM's predictions of rainfall distribution are explained by the effects of topography, orography, and land cover types different from forests. Our results lend a strong observational support to the BiPAM theory at seasonal time scales over South American forested flat lands.

Global and Regional Trends of Aerosol Optical Depth over Land and Ocean Using SeaWiFS Measurements from 1997 to 2010

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Gautam, R.; Sayer, A. M.; Bettenhausen, C.; Li, C.; Jeong, M. J.; Tsay, S. C.; Holben, B. N.

2012-01-01

Both sensor calibration and satellite retrieval algorithm play an important role in the ability to determine accurately long-term trends from satellite data. Owing to the unprecedented accuracy and long-term stability of its radiometric calibration, the SeaWiFS measurements exhibit minimal uncertainty with respect to sensor calibration. In this study, we take advantage of this well-calibrated set of measurements by applying a newly-developed aerosol optical depth (AOD) retrieval algorithm over land and ocean to investigate the distribution of AOD, and to identify emerging patterns and trends in global and regional aerosol loading during its 13-year mission. Our results indicate that the averaged AOD trend over global ocean is weakly positive from 1998 to 2010 and comparable to that observed by MODIS but opposite in sign to that observed by AVHRR during overlapping years. On a smaller scale, different trends are found for different regions. For example, large upward trends are found over the Arabian Peninsula that indicate a strengthening of the seasonal cycle of dust emission and transport processes over the whole region as well as over downwind oceanic regions. In contrast, a negative-neutral tendency is observed over the desert/arid Saharan region as well as in the associated dust outflow over the north Atlantic. Additionally, we found decreasing trends over the eastern US and Europe, and increasing trends over countries such as China and India that are experiencing rapid economic development. In general, these results are consistent with those derived from ground-based AERONET measurements.

LAND USE AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL AND TEMPORAL ASSESSMENT

EPA Science Inventory

We assessed the effects of land-use at multiple spatial scales (e.g., catchment, stream network, and stream reach) on periphyton from 25 wadeable streams along a land-use gradient in the Willamette River Basin, Oregon, in a dry season. Additional water chemistry samples were col...

Generation of High Resolution Land Surface Parameters in the Community Land Model

NASA Astrophysics Data System (ADS)

Ke, Y.; Coleman, A. M.; Wigmosta, M. S.; Leung, L.; Huang, M.; Li, H.

2010-12-01

The Community Land Model (CLM) is the land surface model used for the Community Atmosphere Model (CAM) and the Community Climate System Model (CCSM). It examines the physical, chemical, and biological processes across a variety of spatial and temporal scales. Currently, efforts are being made to improve the spatial resolution of the CLM, in part, to represent finer scale hydrologic characteristics. Current land surface parameters of CLM4.0, in particular plant functional types (PFT) and leaf area index (LAI), are generated from MODIS and calculated at a 0.05 degree resolution. These MODIS-derived land surface parameters have also been aggregated to coarser resolutions (e.g., 0.5, 1.0 degrees). To evaluate the response of CLM across various spatial scales, higher spatial resolution land surface parameters need to be generated. In this study we examine the use of Landsat TM/ETM+ imagery and data fusion techniques for generating land surface parameters at a 1km resolution within the Pacific Northwest United States. . Land cover types and PFTs are classified based on Landsat multi-season spectral information, DEM, National Land Cover Database (NLCD) and the USDA-NASS Crop Data Layer (CDL). For each PFT, relationships between MOD15A2 high quality LAI values, Landsat-based vegetation indices, climate variables, terrain, and laser-altimeter derived vegetation height are used to generate monthly LAI values at a 30m resolution. The high-resolution PFT and LAI data are aggregated to create a 1km model grid resolution. An evaluation and comparison of CLM land surface response at both fine and moderate scale is presented.

High Resolution Land Surface Modeling with the next generation Land Data Assimilation Systems

NASA Astrophysics Data System (ADS)

Kumar, S. V.; Eylander, J.; Peters-Lidard, C.

2005-12-01

Knowledge of land surface processes is important to many real-world applications such as agricultural production, water resources management, and flood predication. The Air Force Weather Agency (AFWA) has provided the USDA and other customers global soil moisture and temperature data for the past 30 years using the agrometeorological data assimilation model (now called AGRMET), merging atmospheric data. Further, accurate initialization of land surface conditions has been shown to greatly influence and improve weather forecast model and seasonal-to-interannual climate predictions. The AFWA AGRMET model exploits real time precipitation observations and analyses, global forecast model and satellite data to generate global estimates of soil moisture, soil temperature and other land surface states at 48km spatial resolution. However, to truly address the land surface initialization and climate prediction problem, and to mitigate the errors introduced by the differences in spatial scales of models, representations of land surface conditions need to be developed at the same fine scales such as that of cloud resolving models. NASA's Goddard Space Flight Center has developed an offline land data assimilation system known as the Land Information System (LIS) capable of modeling land atmosphere interactions at spatial resolutions as fine as 1km. LIS provides a software architecture that integrates the use of the state of the art land surface models, data assimilation techniques, and high performance computing and data management tools. LIS also employs many high resolution surface parameters such as the NASA Earth Observing System (EOS)-era products. In this study we describe the development of a next generation high resolution land surface modeling and data assimilation system, combining the capabilities of LIS and AGRMET. We investigate the influence of high resolution land surface data and observations on the land surface conditions by comparing with the operational AGRMET

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

Land use determinants of small mammal abundance and distribution in a plague endemic area of Lushoto District, Tanzania.

PubMed

Hieronimo, Proches; Kimaro, Didas N; Kihupi, Nganga I; Gulinck, Hubert; Mulungu, Loth S; Msanya, Balthazar M; Leirs, Herwig; Deckers, Jozef A

2014-07-01

Small mammals are considered to be involved in the transmission cycle of bubonic plague, still occurring in different parts of the world, including the Lushoto District in Tanzania. The objective of this study was to determine the relationship between land use types and practices and small mammal abundance and distribution. A field survey was used to collect data in three landscapes differing in plague incidences. Data collection was done both in the wet season (April-June 2012) and dry season (August-October 2012). Analysis of variance and Boosted Regression Trees (BRT) modelling technique were used to establish the relationship between land use and small mammal abundance and distribution. Significant variations (p ≤ 0.05) of small mammal abundance among land use types were identified. Plantation forest with farming, natural forest and fallow had higher populations of small mammals than the other aggregated land use types. The influence of individual land use types on small mammal abundance level showed that, in both dry and wet seasons, miraba and fallow tended to favour small mammals' habitation whereas land tillage practices had the opposite effect. In addition, during the wet season crop types such as potato and maize appeared to positively influence the distribution and abundance of small mammals which was attributed to both shelter and food availability. Based on the findings from this study it is recommended that future efforts to predict and map spatial and temporal human plague infection risk at fine scale should consider the role played by land use and associated human activities on small mammal abundance and distribution.

The Effect of Agricultural Growing Season Change on Market Prices in Africa

NASA Technical Reports Server (NTRS)

deBeurs, K.M.; Brown, M. E.

2013-01-01

to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices