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Sample records for crop area estimate

  1. Area estimation using multiyear designs and partial crop identification

    NASA Technical Reports Server (NTRS)

    Sielken, R. L., Jr.

    1983-01-01

    Progress is reported for the following areas: (1) estimating the stratum's crop acreage proportion using the multiyear area estimation model; (2) assessment of multiyear sampling designs; and (3) development of statistical methodology for incorporating partially identified sample segments into crop area estimation.

  2. Multi crop area estimation in Idaho using EDITOR

    NASA Technical Reports Server (NTRS)

    Sheffner, E. J.

    1984-01-01

    The use of LANDSAT multispectral scanner digital data for multi-crop acreage estimation in the central Snake River Plain of Idaho was examined. Two acquisitions of LANDSAT data covering ground sample units selected from a U.S. Department of Agriculture sampling frame in a four country study site were used to train a maximum likelihood classifier which, subsequently, classified all picture elements in the study site. Acreage estimates for six major crops, by county and for the four counties combined, were generated from the classification using the Battesse-Fuller model for estimation by regression in small areas. Results from the regression analysis were compared to those obtained by direct expansion of the ground data. Using the LANDSAT data significantly decreased the errors associated with the estimates for the three largest acreage crops. The late date of the second LANDSAT acquisition may have contributed to the poor results for three summer crops.

  3. Area estimation using multiyear designs and partial crop identification

    NASA Technical Reports Server (NTRS)

    Sielken, R. L., Jr.

    1984-01-01

    Statistical procedures were developed for large area assessments using both satellite and conventional data. Crop acreages, other ground cover indices, and measures of change were the principal characteristics of interest. These characteristics are capable of being estimated from samples collected possibly from several sources at varying times, with different levels of identification. Multiyear analysis techniques were extended to include partially identified samples; the best current year sampling design corresponding to a given sampling history was determined; weights reflecting the precision or confidence in each observation were identified and utilized, and the variation in estimates incorporating partially identified samples were quantified.

  4. Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery

    NASA Astrophysics Data System (ADS)

    Potgieter, A. B.; Apan, A.; Hammer, G.; Dunn, P.

    To date, industry and crop forecasters have had a good idea of the potential crop yield for a specific season, but early-season information on crop area for a shire or region has been mostly unavailable. The question of "how early and with what accuracy?" area estimates can be determined using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) imagery was investigated in this paper. The study was conducted for two shires in Queensland, Australia for the 2003 and 2004 seasons, and focused on deriving total winter crop area estimates (including wheat, barley and chickpea). A simple metric ( ΔE), which measures the green-up rate of the crop canopy, was derived. Using the unsupervised k-means classification algorithm, the accumulated difference of two consecutive images (one month apart) for three EVI threshold cut-offs ( ΔEi, where i=250, 500 and 750) at monthly intervals from April to October was calculated. July showed the highest pixel accuracy with percent correctly classified for all thresholds of 94% and 98% for 2003 and 2004, respectively. The differences in accuracy between the three cut-offs were minimal and the T500 threshold was selected as the preferred cut-off to avoid measuring too small or too large fluctuations in the differential EVI values. When compared to the aggregated shire data (surveyed) on crop area across shires and seasons, average percent differences for the ΔE for July and August ranged from -19% to 9%. To capture most of the variability in green-up within a region, the average ΔE of July and August was used for the early-season prediction of total winter crop area estimates. This resulted in high accuracy (R 2=0.96; RMSE = 3157 ha) for predicting the total winter crop from 2000 to 2004 across both shires. This result indicated that this simple multi-temporal remote sensing approach could be used with confidence in early-season crop area prediction at least one to two months ahead of

  5. Crop identification and area estimation over large geographic areas using LANDSAT MSS data

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. LANDSAT MSS data was adequate to accurately identify wheat in Kansas; corn and soybean estimates in Indiana were less accurate. Computer-aided analysis techniques were effectively used to extract crop identification information from LANDSAT data. Systematic sampling of entire counties made possible by computer classification methods resulted in very precise area estimates at county, district, and state levels. Training statistics were successfully extended from one county to other counties having similar crops and soils if the training areas sampled the total variation of the area to be classified.

  6. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    USGS Publications Warehouse

    Husak, G.J.; Marshall, M. T.; Michaelsen, J.; Pedreros, Diego; Funk, Christopher C.; Galu, G.

    2008-01-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

  7. Crop area estimation using high and medium resolution satellite imagery in areas with complex topography

    NASA Astrophysics Data System (ADS)

    Husak, G. J.; Marshall, M. T.; Michaelsen, J.; Pedreros, D.; Funk, C.; Galu, G.

    2008-07-01

    Reliable estimates of cropped area (CA) in developing countries with chronic food shortages are essential for emergency relief and the design of appropriate market-based food security programs. Satellite interpretation of CA is an effective alternative to extensive and costly field surveys, which fail to represent the spatial heterogeneity at the country-level. Bias-corrected, texture based classifications show little deviation from actual crop inventories, when estimates derived from aerial photographs or field measurements are used to remove systematic errors in medium resolution estimates. In this paper, we demonstrate a hybrid high-medium resolution technique for Central Ethiopia that combines spatially limited unbiased estimates from IKONOS images, with spatially extensive Landsat ETM+ interpretations, land-cover, and SRTM-based topography. Logistic regression is used to derive the probability of a location being crop. These individual points are then aggregated to produce regional estimates of CA. District-level analysis of Landsat based estimates showed CA totals which supported the estimates of the Bureau of Agriculture and Rural Development. Continued work will evaluate the technique in other parts of Africa, while segmentation algorithms will be evaluated, in order to automate classification of medium resolution imagery for routine CA estimation in the future.

  8. Evaluation of small area crop estimation techniques using LANDSAT- and ground-derived data. [South Dakota

    NASA Technical Reports Server (NTRS)

    Amis, M. L.; Martin, M. V.; Mcguire, W. G.; Shen, S. S. (Principal Investigator)

    1982-01-01

    Studies completed in fiscal year 1981 in support of the clustering/classification and preprocessing activities of the Domestic Crops and Land Cover project. The theme throughout the study was the improvement of subanalysis district (usually county level) crop hectarage estimates, as reflected in the following three objectives: (1) to evaluate the current U.S. Department of Agriculture Statistical Reporting Service regression approach to crop area estimation as applied to the problem of obtaining subanalysis district estimates; (2) to develop and test alternative approaches to subanalysis district estimation; and (3) to develop and test preprocessing techniques for use in improving subanalysis district estimates.

  9. Evaluation of large area crop estimation techniques using LANDSAT and ground-derived data. [Missouri

    NASA Technical Reports Server (NTRS)

    Amis, M. L.; Lennington, R. K.; Martin, M. V.; Mcguire, W. G.; Shen, S. S. (Principal Investigator)

    1981-01-01

    The results of the Domestic Crops and Land Cover Classification and Clustering study on large area crop estimation using LANDSAT and ground truth data are reported. The current crop area estimation approach of the Economics and Statistics Service of the U.S. Department of Agriculture was evaluated in terms of the factors that are likely to influence the bias and variance of the estimator. Also, alternative procedures involving replacements for the clustering algorithm, the classifier, or the regression model used in the original U.S. Department of Agriculture procedures were investigated.

  10. Efficiency assessment of using satellite data for crop area estimation in Ukraine

    NASA Astrophysics Data System (ADS)

    Gallego, Francisco Javier; Kussul, Nataliia; Skakun, Sergii; Kravchenko, Oleksii; Shelestov, Andrii; Kussul, Olga

    2014-06-01

    The knowledge of the crop area is a key element for the estimation of the total crop production of a country and, therefore, the management of agricultural commodities markets. Satellite data and derived products can be effectively used for stratification purposes and a-posteriori correction of area estimates from ground observations. This paper presents the main results and conclusions of the study conducted in 2010 to explore feasibility and efficiency of crop area estimation in Ukraine assisted by optical satellite remote sensing images. The study was carried out on three oblasts in Ukraine with a total area of 78,500 km2. The efficiency of using images acquired by several satellite sensors (MODIS, Landsat-5/TM, AWiFS, LISS-III, and RapidEye) combined with a field survey on a stratified sample of square segments for crop area estimation in Ukraine is assessed. The main criteria used for efficiency analysis are as follows: (i) relative efficiency that shows how much time the error of area estimates can be reduced with satellite images, and (ii) cost-efficiency that shows how much time the costs of ground surveys for crop area estimation can be reduced with satellite images. These criteria are applied to each satellite image type separately, i.e., no integration of images acquired by different sensors is made, to select the optimal dataset. The study found that only MODIS and Landsat-5/TM reached cost-efficiency thresholds while AWiFS, LISS-III, and RapidEye images, due to its high price, were not cost-efficient for crop area estimation in Ukraine at oblast level.

  11. Research on estimation crop planting area by integrating the optical and microwave remote sensing data

    NASA Astrophysics Data System (ADS)

    Liu, Jiang; Yu, Fan; Liu, Dandan; Tian, Jing; Zhang, Weicheng; Wang, Qiang; Yang, Jinling; Zhang, Lei

    2015-12-01

    Considering the problem in monitoring agricultural condition in the semi-arid areas of Northwest of China, we propose a new method for estimation of crop planting area, using the single phase optical and microwave remote sensing data collaboratively, which have demonstrated their respective advantages in the extraction of surface features. In the model, the ASAR backscatter coefficient is normalized by the incident angle at first, then the classifier based on Bayesian network is developed, and the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. Moreover the crop planting areas can be extracted by the classification results. At last, the model is validated for the necessities of normalization by the incident angle and integration of TM and ASAR respectively. It results that the estimation accuracy of crop planting area of corn and other crops garden are 98.47% and 78.25% respectively using the proposed method, with an improvement of estimation accuracy of about 3.28% and 4.18% relative to single TM classification. These illustrate that synthesis of optical and microwave remote sensing data is efficient and potential in estimation crop planting area.

  12. [Estimating Leaf Area Index of Crops Based on Hyperspectral Compact Airborne Spectrographic Imager (CASI) Data].

    PubMed

    Tang, Jian-min; Liao, Qin-hong; Liu, Yi-qing; Yang, Gui-jun; Feng, Hai-kuanr; Wang, Ji-hua

    2015-05-01

    The fast estimation of leaf area index (LAI) is significant for learning the crops growth, monitoring the disease and insect, and assessing the yield of crops. This study used the hyperspectral compact airborne spectrographic imager (CASI) data of Zhangye city, in Heihe River basin, on July 7, 2012, and extracted the spectral reflectance accurately. The potential of broadband and red-edge vegetation index for estimating the LAI of crops was comparatively investigated by combined with the field measured data. On this basis, the sensitive wavebands for estimating the LAI of crops were selected and two new spectral indexes (NDSI and RSI) were constructed, subsequently, the spatial distribution of LAI in study area was analyzed. The result showed that broadband vegetation index NDVI had good effect for estimating the LAI when the vegetation coverage is relatively lower, the R2 and RMSE of estimation model were 0. 52, 0. 45 (p<0. 01) , respectively. For red-edge vegetation index, CIred edge took the different crop types into account fully, thus it gained the same estimation accuracy with NDVI. NDSI(569.00, 654.80) and RSI(597.60, 654.80) were constructed by using waveband combination algorithm, which has superior estimation results than NDVI and CIred edge. The R2 of estimation model used NDSI(569.00, 654.80) was 0. 77(p<0. 000 1), it mainly used the wavebands near the green peak and red valley of vegetation spectrum. The spatial distribution map of LAI was made according to the functional relationship between the NDSI(569.00, 654.80) and LAI. After analyzing this map, the LAI values were lower in the northwest of study area, this indicated that more fertilizer should be increased in this area. This study can provide technical support for the agricultural administrative department to learn the growth of crops quickly and make a suitable fertilization strategy. PMID:26415459

  13. Crop area estimation based on remotely-sensed data with an accurate but costly subsample

    NASA Technical Reports Server (NTRS)

    Gunst, R. F.

    1985-01-01

    Research activities conducted under the auspices of National Aeronautics and Space Administration Cooperative Agreement NCC 9-9 are discussed. During this contract period research efforts are concentrated in two primary areas. The first are is an investigation of the use of measurement error models as alternatives to least squares regression estimators of crop production or timber biomass. The secondary primary area of investigation is on the estimation of the mixing proportion of two-component mixture models. This report lists publications, technical reports, submitted manuscripts, and oral presentation generated by these research efforts. Possible areas of future research are mentioned.

  14. Satellite Estimates of Crop Area and Maize Yield in Zambia's Agricultural Districts

    NASA Astrophysics Data System (ADS)

    Azzari, G.; Lobell, D. B.

    2015-12-01

    Predicting crop yield and area from satellite is a valuable tool to monitor different aspects of productivity dynamics and food security. In Sub-Saharan Africa, where the agricultural landscape is complex and dominated by smallholder systems, such dynamics need to be investigated at the field scale. We leveraged the large data pool and computational power of Google Earth Engine to 1) generate 30 m resolution cover maps of selected provinces of Zambia, 2) estimate crop area, and 3) produce yearly maize yield maps using the recently developed SCYM (Scalable satellite-based Crop Yield Mapper) algorithm. We will present our results and their validation against a ground survey dataset collected yearly by the Zambia Ministry of Agriculture from about 12,500 households.

  15. Leaf area index estimation in different crops: Case study for wheat, maize, soybean, and potato

    NASA Astrophysics Data System (ADS)

    Gitelson, A. A.; Nguy-Robertson, A. L.; Peng, Y.; Arkebauer, T. J.; Pimstein, A.; Herrmann, I.; Karnieli, A.; Rundquist, D. C.; Bonfil, D.

    2012-12-01

    Vegetation indices (VIs) have been shown to be a proxy of green leaf area index (gLAI); however, it has not been verified whether the relationships VI vs. gLAI are the same, as well as VIs retaining their accuracy, for various crop types for estimating gLAI. The goal of this study was to (1) determine if the best VIs used in previous studies for gLAI estimation in maize and soybean may be applicable for potato and wheat and vice versa, and (2) determining the cause of a hysteresis between green up and reproductive stages for the VI vs. gLAI relationship. Spectral measurements of wheat and potato were obtained in Israel and of maize and soybean in the USA. In Israel, remote estimates of gLAI were compared with in-situ canopy transmittance measurements of irrigated potato and wheat under various nitrogen treatments from 2004-2007 for a total of 15 field-years. In eastern Nebraska, USA, remote estimates of maize and soybean gLAI data were compared with destructive gLAI determination in two irrigated/rainfed maize/soybean rotation sites and in one irrigated site under continuous maize. These data were collected during eight years (2001-2008) for a total of 24 field-years. For all four crops, the ten VIs examined showed similarities in relationships between VIs and gLAI with the exception of Red-edge Inflection Point (REIP) and the MERIS Terrestrial Chlorophyll Index (MTCI). REIP and MTCI have very different relationships with maize and soybean gLAI in green up and reproductive stages, thus, they require re-parameterization during the season. This study outlines the two major factors that influence the VI vs. gLAI relationship in the green up and reproductive stages. While the results suggest that relationships VI vs. gLAI are quite close for all four crops, different methodologies in determining the ground-truth measurements of gLAI prevent us to confirm whether algorithms calibrated for one crop can be used with no re-parameterization for other crops. These concerns

  16. Estimating Hydrologic Fluxes, Crop Water Use, and Agricultural Land Area in China using Data Assimilation

    NASA Astrophysics Data System (ADS)

    Smith, Tiziana; McLaughlin, Dennis B.; Hoisungwan, Piyatida

    2016-04-01

    Crop production has significantly altered the terrestrial environment by changing land use and by altering the water cycle through both co-opted rainfall and surface water withdrawals. As the world's population continues to grow and individual diets become more resource-intensive, the demand for food - and the land and water necessary to produce it - will continue to increase. High-resolution quantitative data about water availability, water use, and agricultural land use are needed to develop sustainable water and agricultural planning and policies. However, existing data covering large areas with high resolution are susceptible to errors and can be physically inconsistent. China is an example of a large area where food demand is expected to increase and a lack of data clouds the resource management dialogue. Some assert that China will have insufficient land and water resources to feed itself, posing a threat to global food security if they seek to increase food imports. Others believe resources are plentiful. Without quantitative data, it is difficult to discern if these concerns are realistic or overly dramatized. This research presents a quantitative approach using data assimilation techniques to characterize hydrologic fluxes, crop water use (defined as crop evapotranspiration), and agricultural land use at 0.5 by 0.5 degree resolution and applies the methodology in China using data from around the year 2000. The approach uses the principles of water balance and of crop water requirements to assimilate existing data with a least-squares estimation technique, producing new estimates of water and land use variables that are physically consistent while minimizing differences from measured data. We argue that this technique for estimating water fluxes and agricultural land use can provide a useful basis for resource management modeling and policy, both in China and around the world.

  17. Crop area estimation based on remotely-sensed data with an accurate but costly subsample

    NASA Technical Reports Server (NTRS)

    Gunst, R. F.

    1983-01-01

    Alternatives to sampling-theory stratified and regression estimators of crop production and timber biomass were examined. An alternative estimator which is viewed as especially promising is the errors-in-variable regression estimator. Investigations established the need for caution with this estimator when the ratio of two error variances is not precisely known.

  18. Peatlands under cultivation for arable crops; a new area estimate for Ireland

    NASA Astrophysics Data System (ADS)

    Donlan, Jennifer; Byrne, Ken

    2015-04-01

    Peatlands cover 20% of the Irish landscape and store between 53% and 61% of total soil carbon stocks. Eighty percent of these have been drained for peat cutting, afforestation and conversion to agricultural use. As a signatory to the United Nations framework Convention on Climate Change, Ireland is required to make an annual inventory of greenhouse gas emissions and sinks in the agricultural sector. While guidelines on the compilation of such inventories are provided by the IPCC 2006 Guidelines, reporting at higher Tiers requires the collection of national specific information including the accuracy of inventories. Total land area (including accuracy estimates) and national emission factors are lacking for agricultural activity on drained organic soils i.e. converted peatlands. Locations of organic (peat) soils under cultivation were identified using a map overlay analysis and existing geographic data on peat habitats and agricultural activities. The result was 3688 ha of land cultivated for arable crops overlaid areas classified as peatland. A design-based accuracy assessment and probability sampling method were chosen to assess the accuracy of the overlay. The focus of the analysis was on the accuracy of the peat data. The agricultural data was considered quite robust, so it was used to limit the area included in the assessment. Ground truthing was carried out at randomly chosen locations within areas mapped as 1) areas cultivated for arable crops and 2) peat habitats or a 100m buffer surrounding those areas. Sixty-nine sites were sampled and an error matrix was constructed comparing the map classification at the sample location to the samples taken there. The overall accuracy was 77%. There was a high producer's accuracy (84%) and a low user's accuracy (28%) for the peat category. Area estimate of peatlands under cultivation for arable crops was 1235 ± 784 ha. Future policies will require the identification of strategies to reduce greenhouse gas emissions and

  19. Georeferenced Scanning System to Estimate the Leaf Wall Area in Tree Crops

    PubMed Central

    del-Moral-Martínez, Ignacio; Arnó, Jaume; Escolà, Alexandre; Sanz, Ricardo; Masip-Vilalta, Joan; Company-Messa, Joaquim; Rosell-Polo, Joan R.

    2015-01-01

    This paper presents the use of a terrestrial light detection and ranging (LiDAR) system to scan the vegetation of tree crops to estimate the so-called pixelated leaf wall area (PLWA). Scanning rows laterally and considering only the half-canopy vegetation to the line of the trunks, PLWA refers to the vertical projected area without gaps detected by LiDAR. As defined, PLWA may be different depending on the side from which the LiDAR is applied. The system is completed by a real-time kinematic global positioning system (RTK-GPS) sensor and an inertial measurement unit (IMU) sensor for positioning. At the end, a total leaf wall area (LWA) is computed and assigned to the X, Y position of each vertical scan. The final value of the area depends on the distance between two consecutive scans (or horizontal resolution), as well as the number of intercepted points within each scan, since PLWA is only computed when the laser beam detects vegetation. To verify system performance, tests were conducted related to the georeferencing task and synchronization problems between GPS time and central processing unit (CPU) time. Despite this, the overall accuracy of the system is generally acceptable. The Leaf Area Index (LAI) can then be estimated using PLWA as an explanatory variable in appropriate linear regression models. PMID:25868079

  20. Georeferenced scanning system to estimate the leaf wall area in tree crops.

    PubMed

    del-Moral-Martínez, Ignacio; Arnó, Jaume; Escolà, Alexandre; Sanz, Ricardo; Masip-Vilalta, Joan; Company-Messa, Joaquim; Rosell-Polo, Joan R

    2015-01-01

    This paper presents the use of a terrestrial light detection and ranging (LiDAR) system to scan the vegetation of tree crops to estimate the so-called pixelated leaf wall area (PLWA). Scanning rows laterally and considering only the half-canopy vegetation to the line of the trunks, PLWA refers to the vertical projected area without gaps detected by LiDAR. As defined, PLWA may be different depending on the side from which the LiDAR is applied. The system is completed by a real-time kinematic global positioning system (RTK-GPS) sensor and an inertial measurement unit (IMU) sensor for positioning. At the end, a total leaf wall area (LWA) is computed and assigned to the X, Y position of each vertical scan. The final value of the area depends on the distance between two consecutive scans (or horizontal resolution), as well as the number of intercepted points within each scan, since PLWA is only computed when the laser beam detects vegetation. To verify system performance, tests were conducted related to the georeferencing task and synchronization problems between GPS time and central processing unit (CPU) time. Despite this, the overall accuracy of the system is generally acceptable. The Leaf Area Index (LAI) can then be estimated using PLWA as an explanatory variable in appropriate linear regression models. PMID:25868079

  1. Estimating plant area index for monitoring crop growth dynamics using Landsat-8 and RapidEye images

    NASA Astrophysics Data System (ADS)

    Shang, Jiali; Liu, Jiangui; Huffman, Ted; Qian, Budong; Pattey, Elizabeth; Wang, Jinfei; Zhao, Ting; Geng, Xiaoyuan; Kroetsch, David; Dong, Taifeng; Lantz, Nicholas

    2014-01-01

    This study investigates the use of two different optical sensors, the multispectral imager (MSI) onboard the RapidEye satellites and the operational land imager (OLI) onboard the Landsat-8 for mapping within-field variability of crop growth conditions and tracking the seasonal growth dynamics. The study was carried out in southern Ontario, Canada, during the 2013 growing season for three annual crops, corn, soybeans, and winter wheat. Plant area index (PAI) was measured at different growth stages using digital hemispherical photography at two corn fields, two winter wheat fields, and two soybean fields. Comparison between several conventional vegetation indices derived from concurrently acquired image data by the two sensors showed a good agreement. The two-band enhanced vegetation index (EVI2) and the normalized difference vegetation index (NDVI) were derived from the surface reflectance of the two sensors. The study showed that EVI2 was more resistant to saturation at high biomass range than NDVI. A linear relationship could be used for crop green effective PAI estimation from EVI2, with a coefficient of determination (R2) of 0.85 and root-mean-square error of 0.53. The estimated multitemporal product of green PAI was found to be able to capture the seasonal dynamics of the three crops.

  2. Assimilating Leaf Area Index Estimates from Remote Sensing into the Simulations of a Cropping Systems Model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spatial extrapolation of cropping systems models for regional crop growth and water use assessment and farm-level precision management has been limited by the vast model input requirements and the model sensitivity to parameter uncertainty. Remote sensing has been proposed as a viable source of spat...

  3. Multi-crop area estimation and mapping on a microprocessor/mainframe network

    NASA Technical Reports Server (NTRS)

    Sheffner, E.

    1985-01-01

    The data processing system is outlined for a 1985 test aimed at determining the performance characteristics of area estimation and mapping procedures connected with the California Cooperative Remote Sensing Project. The project is a joint effort of the USDA Statistical Reporting Service-Remote Sensing Branch, the California Department of Water Resources, NASA-Ames Research Center, and the University of California Remote Sensing Research Program. One objective of the program was to study performance when data processing is done on a microprocessor/mainframe network under operational conditions. The 1985 test covered the hardware, software, and network specifications and the integration of these three components. Plans for the year - including planned completion of PEDITOR software, testing of software on MIDAS, and accomplishment of data processing on the MIDAS-VAX-CRAY network - are discussed briefly.

  4. Two phase sampling for wheat acreage estimation. [large area crop inventory experiment

    NASA Technical Reports Server (NTRS)

    Thomas, R. W.; Hay, C. M.

    1977-01-01

    A two phase LANDSAT-based sample allocation and wheat proportion estimation method was developed. This technique employs manual, LANDSAT full frame-based wheat or cultivated land proportion estimates from a large number of segments comprising a first sample phase to optimally allocate a smaller phase two sample of computer or manually processed segments. Application to the Kansas Southwest CRD for 1974 produced a wheat acreage estimate for that CRD within 2.42 percent of the USDA SRS-based estimate using a lower CRD inventory budget than for a simulated reference LACIE system. Factor of 2 or greater cost or precision improvements relative to the reference system were obtained.

  5. Spectral procedures for estimating crop biomass

    SciTech Connect

    Wanjura, D.F.; Hatfield, J.L.

    1985-05-01

    Spectral reflectance was measured semi-weekly and used to estimate leaf area and plant dry weight accumulation in cotton, soybeans, and sunflower. Integration of spectral crop growth cycle curves explained up to 95 and 91%, respectively, of the variation in cotton lint yield and dry weight. A theoretical relationship for dry weight accumulation, in which only intercepted radiation or intercepted radiation and solar energy to biomass conversion efficiency were spectrally estimated, explained 99 and 96%, respectively, of the observed plant dry weight variation of the three crops. These results demonstrate the feasibility of predicting crop biomass from spectral measurements collected frequently during the growing season. 15 references.

  6. Crop monitoring using remote sensing orientated for government decision making and agricultural management: a case study of China's soybean planting area estimation

    NASA Astrophysics Data System (ADS)

    Yang, Bangjie; Qian, Yonglan; Pei, Zhiyuan; Jiao, Xianfeng

    2006-12-01

    China is one of the main soybean production countries in the world and soybean is of great importance in agricultural industry, domestic consumption and international trade. In recent years, however, China has become the largest soybean importer in the world. Therefore timely credible information about soybean planting area and production is essential for government decision making and agricultural management on domestic consumption and international trade. Moreover, information on soybean planting and continuous planting location is critical for distributing farmer subsidies and production management. In this paper, an operational system based on multi-resolution remotely sensed data was developed for the soybean area inventory and continuous cropping area monitoring. A stratified sampling method is employed to extract and locate major soybean-planting regions, which are later surveyed using remote sensing data. At the same time, sub regions are constructed based on cropping systems in which remotely sensed data of different resolutions are applied for the soybean area estimation and replanting area location assessment.

  7. Estimation of flood losses to agricultural crops using remote sensing

    NASA Astrophysics Data System (ADS)

    Tapia-Silva, Felipe-Omar; Itzerott, Sibylle; Foerster, Saskia; Kuhlmann, Bernd; Kreibich, Heidi

    2011-01-01

    The estimation of flood damage is an important component of risk-oriented flood design, risk mapping, financial appraisals and comparative risk analyses. However, research on flood loss modelling, especially in the agricultural sector, has not yet gained much attention. Agricultural losses strongly depend on the crops affected, which need to be predicted accurately. Therefore, three different methods to predict flood-affected crops using remote sensing and ancillary data were developed, applied and validated. These methods are: (a) a hierarchical classification based on standard curves of spectral response using satellite images, (b) disaggregation of crop statistics using a Monte Carlo simulation and probabilities of crops to be cultivated on specific soils and (c) analysis of crop rotation with data mining Net Bayesian Classifiers (NBC) using soil data and crop data derived from a multi-year satellite image analysis. A flood loss estimation model for crops was applied and validated in flood detention areas (polders) at the Havel River (Untere Havelniederung) in Germany. The polders were used for temporary storage of flood water during the extreme flood event in August 2002. The flood loss to crops during the extreme flood event in August 2002 was estimated based on the results of the three crop prediction methods. The loss estimates were then compared with official loss data for validation purposes. The analysis of crop rotation with NBC obtained the best result, with 66% of crops correctly classified. The accuracy of the other methods reached 34% with identification using Normalized Difference Vegetation Index (NDVI) standard curves and 19% using disaggregation of crop statistics. The results were confirmed by evaluating the loss estimation procedure, in which the damage model using affected crops estimated by NBC showed the smallest overall deviation (1%) when compared to the official losses. Remote sensing offers various possibilities for the improvement of

  8. Vegetation monitoring and estimation of evapotranspiration using remote sensing-based models in heterogeneous areas with patchy natural vegetation and crops

    NASA Astrophysics Data System (ADS)

    Carpintero, Elisabet; Andreu, Ana; Gonzalez-Dugo, Maria P.

    2015-04-01

    The integration of remotely sensed data into models for estimating evapotranspiration (ET) has increased significantly in recent years, allowing the extension of these models application from point to regional scale. Remote sensors provide distributed information about the status of vegetation and allow for a regular monitoring of water consumption. Currently, there are two types of approaches for estimating ET based either on the soil water balance, or surface energy balance. The first one uses the reflectance of vegetated surfaces in the visible and near infrared regions of the electromagnetic spectrum (VIS / NIR) to characterize the vegetation and its role in the water balance (Gonzalez-Dugo and Mateos, 2008). On the other hand, thermal-based energy balance models use the radiometric surface temperature registered by the sensor on thermal infrared (TIR) bands as the primary boundary condition for estimating ET (Kustas and Norman, 1996). The aim of this work is to carry out, using Landsat-8 satellite images, a continuous monitoring of growth and evapotranspiration of the different vegetation types, both natural and cultivated, in a region located in Southern Spain during the season August 2013 / September 2014. The region, with about 13800 ha, is marked by strong contrasts in the physical environment, with significant altitudinal gradient combined with a great variety of soil types and vegetation. It is characterized by a variation of grassland, scrubs, conifers, oaks and irrigated crops. In this work, a daily soil water balance has been applied using the vegetation index-basal crop coefficient approach (RSWB). This model is based on FAO-56 methodology (Allen et al., 1998), which determines the evapotranspiration of vegetation with the concepts of crop coefficient and reference ET. The crop coefficient accounts for the influence of the plants on the evapotranspiration, considering the effect of changes in canopy biophysical properties throughout the growth cycle

  9. Estimating Canopy Dark Respiration for Crop Models

    NASA Technical Reports Server (NTRS)

    Monje Mejia, Oscar Alberto

    2014-01-01

    Crop production is obtained from accurate estimates of daily carbon gain.Canopy gross photosynthesis (Pgross) can be estimated from biochemical models of photosynthesis using sun and shaded leaf portions and the amount of intercepted photosyntheticallyactive radiation (PAR).In turn, canopy daily net carbon gain can be estimated from canopy daily gross photosynthesis when canopy dark respiration (Rd) is known.

  10. Large Area Crop Inventory Experiment (LACIE). Phase 1: Evaluation report

    NASA Technical Reports Server (NTRS)

    1976-01-01

    It appears that the Large Area Crop Inventory Experiment over the Great Plains, can with a reasonable expectation, be a satisfactory component of a 90/90 production estimator. The area estimator produced more accurate area estimates for the total winter wheat region than for the mixed spring and winter wheat region of the northern Great Plains. The accuracy does appear to degrade somewhat in regions of marginal agriculture where there are small fields and abundant confusion crops. However, it would appear that these regions tend also to be marginal with respect to wheat production and thus increased area estimation errors do not greatly influence the overall production estimation accuracy in the United States. The loss of segments resulting from cloud cover appears to be a random phenomenon that introduces no significant bias into the estimates. This loss does increase the variance of the estimates.

  11. Determining crop acreage estimates for specific winter crops using shape attributes from sequential MODIS imagery

    NASA Astrophysics Data System (ADS)

    Potgieter, A. B.; Lawson, K.; Huete, A. R.

    2013-08-01

    There are increasing societal and plant industry demands for more accurate, objective and near real-time crop production information to meet both economic and food security concerns. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to monitor large agricultural areas at acceptable pixel scale, cost and accuracy. Fitting parametric profiles to growing season vegetation index time series reduces the volume of data and provides simple quantitative parameters that relates to crop phenology (sowing date, flowering). In this study, we modelled various Gaussian profiles to time sequential MODIS enhanced vegetation index (EVI) images over winter crops in Queensland, Australia. Three simple Gaussian models were evaluated in their effectiveness to identify and classify various winter crop types and coverage at both pixel and regional scales across Queensland's main agricultural areas. Equal to or greater than 93% classification accuracies were obtained in determining crop acreage estimates at pixel scale for each of the Gaussian modelled approaches. Significant high to moderate correlations (log-linear transformation) were also obtained for determining total winter crop (R2 = 0.93) areas as well as specific crop acreage for wheat (R2 = 0.86) and barley (R2 = 0.83). Conversely, it was much more difficult to predict chickpea acreage (R2 ≤ 0.26), mainly due to very large uncertainties in survey data. The quantitative approach utilised here further had additional benefits of characterising crop phenology in terms of length of growing season and providing regression diagnostics of how well the fitted profiles matched the EVI time series. The Gaussian curve models utilised here are novel in application and therefore will enhance the use and adoption of remote sensing technologies in targeted agricultural application. With innate simplicity and accuracies comparable to other

  12. Assessing the MODIS Crop Detection Algorithm for Soybean Crop Area Mapping and Expansion in the Mato Grosso State, Brazil

    PubMed Central

    Ricardo Ducati, Jorge; da Silveira, Luiz Gonzaga

    2014-01-01

    Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, with R2 = 0.97 and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state. PMID:24983007

  13. Assessing the MODIS crop detection algorithm for soybean crop area mapping and expansion in the Mato Grosso state, Brazil.

    PubMed

    Gusso, Anibal; Arvor, Damien; Ducati, Jorge Ricardo; Veronez, Mauricio Roberto; da Silveira, Luiz Gonzaga

    2014-01-01

    Estimations of crop area were made based on the temporal profiles of the Enhanced Vegetation Index (EVI) obtained from moderate resolution imaging spectroradiometer (MODIS) images. Evaluation of the ability of the MODIS crop detection algorithm (MCDA) to estimate soybean crop areas was performed for fields in the Mato Grosso state, Brazil. Using the MCDA approach, soybean crop area estimations can be provided for December (first forecast) using images from the sowing period and for February (second forecast) using images from the sowing period and the maximum crop development period. The area estimates were compared to official agricultural statistics from the Brazilian Institute of Geography and Statistics (IBGE) and from the National Company of Food Supply (CONAB) at different crop levels from 2000/2001 to 2010/2011. At the municipality level, the estimates were highly correlated, with R (2) = 0.97 and RMSD = 13,142 ha. The MCDA was validated using field campaign data from the 2006/2007 crop year. The overall map accuracy was 88.25%, and the Kappa Index of Agreement was 0.765. By using pre-defined parameters, MCDA is able to provide the evolution of annual soybean maps, forecast of soybean cropping areas, and the crop area expansion in the Mato Grosso state.

  14. Large Area Crop Inventory Experiment (LACIE). Feasibility of assessing crop condition and yield from LANDSAT data

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The author has identified the following significant results. Yield modelling for crop production estimation derived a means of predicting the within-a-year yield and the year-to-year variability of yield over some fixed or randomly located unit of area. Preliminary studies indicated that the requirements for interpreting LANDSAT data for yield may be sufficiently similar to those of signature extension that it is feasible to investigate the automated estimation of production. The concept of an advanced yield model consisting of both spectral and meteorological components was endorsed. Rationale for using meteorological parameters originated from known between season and near harvest dynamics in crop environmental-condition-yield relationships.

  15. The Large Area Crop Inventory Experiment (LACIE)

    NASA Technical Reports Server (NTRS)

    Macdonald, R. B.

    1976-01-01

    A Large Area Crop Inventory Experiment (LACIE) was undertaken to prove out an economically important application of remote sensing from space. The experiment focused upon determination of wheat acreages in the U.S. Great Plains and upon the development and testing of yield models. The results and conclusions are presented.

  16. Large Area Crop Inventory Experiment (LACIE). Phase 2 evaluation report

    NASA Technical Reports Server (NTRS)

    1977-01-01

    Documentation of the activities of the Large Area Crop Inventory Experiment during the 1976 Northern Hemisphere crop year is presented. A brief overview of the experiment is included as well as phase two area, yield, and production estimates for the United States Great Plains, Canada, and the Union of Soviet Socialist Republics spring winter wheat regions. The accuracies of these estimates are compared with independent government estimates. Accuracy assessment of the United States Great Plains yardstick region based on a through blind sight analysis is given, and reasons for variations in estimating performance are discussed. Other phase two technical activities including operations, exploratory analysis, reporting, methods of assessment, phase three and advanced system design, technical issues, and developmental activities are also included.

  17. Preliminary evaluation of spectral, normal and meteorological crop stage estimation approaches

    NASA Technical Reports Server (NTRS)

    Cate, R. B.; Artley, J. A.; Doraiswamy, P. C.; Hodges, T.; Kinsler, M. C.; Phinney, D. E.; Sestak, M. L. (Principal Investigator)

    1980-01-01

    Several of the projects in the AgRISTARS program require crop phenology information, including classification, acreage and yield estimation, and detection of episodal events. This study evaluates several crop calendar estimation techniques for their potential use in the program. The techniques, although generic in approach, were developed and tested on spring wheat data collected in 1978. There are three basic approaches to crop stage estimation: historical averages for an area (normal crop calendars), agrometeorological modeling of known crop-weather relationships agrometeorological (agromet) crop calendars, and interpretation of spectral signatures (spectral crop calendars). In all, 10 combinations of planting and biostage estimation models were evaluated. Dates of stage occurrence are estimated with biases between -4 and +4 days while root mean square errors range from 10 to 15 days. Results are inconclusive as to the superiority of any of the models and further evaluation of the models with the 1979 data set is recommended.

  18. Large Area Crop Inventory Experiment (LACIE). Executive summary

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The author has identified the following significant results. The Large Area Crop Inventory Experiment (LACIE), completed June 30, 1978, has met the USDA at-harvest goals (90% accuracy with a 90% confidence level) in the US Great Plains and U.S.S.R. for two consecutive years. In addition, in the U.S.S.R., LACIE indicated a shortfall in the '76-'77 wheat crop about two months prior to harvest, thus demonstrating the capability of LACIE to make accurate preharvest estimates.

  19. Independent Peer Evaluation of the Large Area Crop Inventory Experiment (LACIE): The LACIE Symposium

    NASA Technical Reports Server (NTRS)

    1978-01-01

    Yield models and crop estimate accuracy are discussed within the Large Area Crop Inventory Experiment. The wheat yield estimates in the United States, Canada, and U.S.S.R. are emphasized. Experimental results design, system implementation, data processing systems, and applications were considered.

  20. Unsupervised linear unmixing of hyperspectral image for crop yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Multispectral and hyperspectral imagery are often used for estimating crop yield. This paper describes an unsupervised unmixing scheme of hyperspectral images to estimate crop yield. From the hyperspectral images, the endmembers and their abundance maps are computed by unsupervised unmixing. The abu...

  1. Large area crop inventory experiment crop assessment subsystem software requirements document

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The functional data processing requirements are described for the Crop Assessment Subsystem of the Large Area Crop Inventory Experiment. These requirements are used as a guide for software development and implementation.

  2. Estimating Phenology Of Agricultural Crops From Space

    NASA Astrophysics Data System (ADS)

    Lopez-Sanchez, Juan M.; Vicente-Guijalba, Fernando; Ballester-Berman, J. David; Cloude, Shane R.

    2013-12-01

    This paper summarises the main results derived from a study developed under the ESA funded PolSAR-Ap project, aimed to demonstrate the contribution of SAR polarimetry in diverse Earth observation products. The specific application treated here is the retrieval of phenology of agricultural crops by exploiting C-band polarimetric images. Using a set of 20 images acquired by Radarsat-2 during the AgriSAR2009 campaign, we show the sensitivity of polarimetry for some crop types (mainly cereals) and present a number of retrieval results with simple algorithms that exhibit excellent performance for some crops, e.g. barley and wheat.

  3. The California Biomass Crop Adoption Model estimates biofuel feedstock crop production across diverse agro-ecological zones within the state, under different future climates

    NASA Astrophysics Data System (ADS)

    Kaffka, S.; Jenner, M.; Bucaram, S.; George, N.

    2012-12-01

    Both regulators and businesses need realistic estimates for the potential production of biomass feedstocks for biofuels and bioproducts. This includes the need to understand how climate change will affect mid-tem and longer-term crop performance and relative advantage. The California Biomass Crop Adoption Model is a partial mathematical programming optimization model that estimates the profit level needed for new crop adoption, and the crop(s) displaced when a biomass feedstock crop is added to the state's diverse set of cropping systems, in diverse regions of the state. Both yield and crop price, as elements of profit, can be varied. Crop adoption is tested against current farmer preferences derived from analysis of 10 years crop production data for all crops produced in California, collected by the California Department of Pesticide Regulation. Analysis of this extensive data set resulted in 45 distinctive, representative farming systems distributed across the state's diverse agro-ecological regions. Estimated yields and water use are derived from field trials combined with crop simulation, reported elsewhere. Crop simulation is carried out under different weather and climate assumptions. Besides crop adoption and displacement, crop resource use is also accounted, derived from partial budgets used for each crop's cost of production. Systematically increasing biofuel crop price identified areas of the state where different types of crops were most likely to be adopted. Oilseed crops like canola that can be used for biodiesel production had the greatest potential to be grown in the Sacramento Valley and other northern regions, while sugar beets (for ethanol) had the greatest potential in the northern San Joaquin Valley region, and sweet sorghum in the southern San Joaquin Valley. Up to approximately 10% of existing annual cropland in California was available for new crop adoption. New crops are adopted if the entire cropping system becomes more profitable. In

  4. Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China

    DOE PAGES

    Ye, Qing; Yang, Xiaoguang; Dai, Shuwei; Chen, Guangsheng; Li, Yong; Zhang, Caixia

    2015-06-05

    Here, we discuss that rice is one of the main crops grown in southern China. Global climate change has significantly altered the local water availability and temperature regime for rice production. In this study, we explored the influence of climate change on suitable rice cropping areas, rice cropping systems and crop water requirements (CWRs) during the growing season for historical (from 1951 to 2010) and future (from 2011 to 2100) time periods. The results indicated that the land areas suitable for rice cropping systems shifted northward and westward from 1951 to 2100 but with different amplitudes.

  5. On the error in crop acreage estimation using satellite (LANDSAT) data

    NASA Technical Reports Server (NTRS)

    Chhikara, R. (Principal Investigator)

    1983-01-01

    The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.

  6. Advancing Methods for Estimating Cropland Area

    NASA Astrophysics Data System (ADS)

    King, L.; Hansen, M.; Stehman, S. V.; Adusei, B.; Potapov, P.; Krylov, A.

    2014-12-01

    Measurement and monitoring of complex and dynamic agricultural land systems is essential with increasing demands on food, feed, fuel and fiber production from growing human populations, rising consumption per capita, the expansion of crops oils in industrial products, and the encouraged emphasis on crop biofuels as an alternative energy source. Soybean is an important global commodity crop, and the area of land cultivated for soybean has risen dramatically over the past 60 years, occupying more than 5% of all global croplands (Monfreda et al 2008). Escalating demands for soy over the next twenty years are anticipated to be met by an increase of 1.5 times the current global production, resulting in expansion of soybean cultivated land area by nearly the same amount (Masuda and Goldsmith 2009). Soybean cropland area is estimated with the use of a sampling strategy and supervised non-linear hierarchical decision tree classification for the United States, Argentina and Brazil as the prototype in development of a new methodology for crop specific agricultural area estimation. Comparison of our 30 m2 Landsat soy classification with the National Agricultural Statistical Services Cropland Data Layer (CDL) soy map shows a strong agreement in the United States for 2011, 2012, and 2013. RapidEye 5m2 imagery was also classified for soy presence and absence and used at the field scale for validation and accuracy assessment of the Landsat soy maps, describing a nearly 1 to 1 relationship in the United States, Argentina and Brazil. The strong correlation found between all products suggests high accuracy and precision of the prototype and has proven to be a successful and efficient way to assess soybean cultivated area at the sub-national and national scale for the United States with great potential for application elsewhere.

  7. Rice Yield Estimation Through Assimilating Satellite Data Into a Crop Simumlation Model

    NASA Astrophysics Data System (ADS)

    Son, N. T.; Chen, C. F.; Chen, C. R.; Chang, L. Y.; Chiang, S. H.

    2016-06-01

    Rice is globally the most important food crop, feeding approximately half of the world's population, especially in Asia where around half of the world's poorest people live. Thus, advanced spatiotemporal information of rice crop yield during crop growing season is critically important for crop management and national food policy making. The main objective of this study was to develop an approach to integrate remotely sensed data into a crop simulation model (DSSAT) for rice yield estimation in Taiwan. The data assimilation was processed to integrate biophysical parameters into DSSAT model for rice yield estimation using the particle swarm optimization (PSO) algorithm. The cost function was constructed based on the differences between the simulated leaf area index (LAI) and MODIS LAI, and the optimization process starts from an initial parameterization and accordingly adjusts parameters (e.g., planting date, planting population, and fertilizer amount) in the crop simulation model. The fitness value obtained from the cost function determined whether the optimization algorithm had reached the optimum input parameters using a user-defined tolerance. The results of yield estimation compared with the government's yield statistics indicated the root mean square error (RMSE) of 11.7% and mean absolute error of 9.7%, respectively. This study demonstrated the applicability of satellite data assimilation into a crop simulation model for rice yield estimation, and the approach was thus proposed for crop yield monitoring purposes in the study region.

  8. Crop gross primary productivity estimation using Landsat and MODIS data

    NASA Astrophysics Data System (ADS)

    Peng, Y.; Gitelson, A. A.; Sakamoto, T.; Masek, J. G.; Rundquist, D. C.; Verma, S. B.; Suyker, A. E.; Baker, J. M.; Hatfield, J.; Meyers, T. P.

    2012-12-01

    In this study, a paradigm was considered to assess gross primary productivity (GPP) in crops via the estimation of total crop chlorophyll (Chl) content. Based on this paradigm, a simple model was developed to estimate crop GPP using a product of Chl-related vegetation index (VI), retrieved from MODIS 250 m and Landsat data, and potential photosynthetically active radiation (PAR). Potential PAR is incident photosynthetically active radiation under a condition of minimal atmospheric aerosol loading. This model is based entirely on satellite data, and it was tested for maize and soybean GPP estimation, which are contrasting crop types different in leaf structures and canopy architectures, under different crop managements and climatic conditions. Using Landsat data, this model was able to accurately estimate GPP in maize-soybean croplands in Mead, Nebraska during growing seasons 2001 through 2008. The indices using green and NIR Landsat bands were found to be the most accurate in GPP estimation with coefficients of variation (CV) below 13% for maize and 15% for soybean. The algorithms established in the Nebraska AmeriFlux sites were validated for the same crops in AmeriFlux sites in Minnesota, Iowa and Illinois. Using MODIS 250 m data, with much higher temporal resolution than Landsat data, the model was capable of estimating GPP accurately in both irrigated and rainfed croplands. Among the MODIS-250 m retrieved indices tested, EVI and WDRVI were the most accurate for GPP estimation with CV below 20% in maize and 25% in soybean. It showed that the developed model was quite sensitive to detect GPP variation in crops where total Chl content is closely tied to seasonal dynamic of GPP.

  9. Cropping frequency and area response to climate variability can exceed yield response

    NASA Astrophysics Data System (ADS)

    Cohn, Avery S.; Vanwey, Leah K.; Spera, Stephanie A.; Mustard, John F.

    2016-06-01

    The sensitivity of agricultural output to climate change has often been estimated by modelling crop yields under climate change scenarios or with statistical analysis of the impacts of year-to-year climatic variability on crop yields. However, the area of cropland and the number of crops harvested per growing season (cropping frequency) both also affect agricultural output and both also show sensitivity to climate variability and change. We model the change in agricultural output associated with the response of crop yield, crop frequency and crop area to year-to-year climate variability in Mato Grosso (MT), Brazil, a key agricultural region. Roughly 70% of the change in agricultural output caused by climate was determined by changes in frequency and/or changes in area. Hot and wet conditions were associated with the largest losses and cool and dry conditions with the largest gains. All frequency and area effects had the same sign as total effects, but this was not always the case for yield effects. A focus on yields alone may therefore bias assessments of the vulnerability of agriculture to climate change. Efforts to reduce climate impacts to agriculture should seek to limit production losses not only from crop yield, but also from changes in cropland area and cropping frequency.

  10. Evaluation of crop acreage estimation methods using Landsat data as auxiliary input

    NASA Technical Reports Server (NTRS)

    Chhikara, R. S.; Houston, A. G.; Lundgren, J. C.

    1985-01-01

    The regression and ratio estimators are studied in the context of improving upon the ground survey estimates of crop acreages by utilizing Landsat data. The approach is to formulate analytically the estimation problem that utilizes ground survey data, as collected by the U.S. Department of Agriculture, and Landsat data, which provide a complete coverage for an area of interest, and then to conduct simulation studies. It is shown over a wide range of conditions that the regression estimator is the most efficient unless there is a low correlation between the actual and estimated crop acreages in the sampled area segments, in which case a ratio type estimator is superior. Estimation of the variance of the regression estimator is also investigated.

  11. The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments.

    PubMed

    Bugbee, B; Monje, O

    1992-01-01

    Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

  12. The limits of crop productivity: validating theoretical estimates and determining the factors that limit crop yields in optimal environments

    NASA Technical Reports Server (NTRS)

    Bugbee, B.; Monje, O.

    1992-01-01

    Plant scientists have sought to maximize the yield of food crops since the beginning of agriculture. There are numerous reports of record food and biomass yields (per unit area) in all major crop plants, but many of the record yield reports are in error because they exceed the maximal theoretical rates of the component processes. In this article, we review the component processes that govern yield limits and describe how each process can be individually measured. This procedure has helped us validate theoretical estimates and determine what factors limit yields in optimal environments.

  13. Estimation of crop coefficients by means of optimized vegetation indices for corn

    NASA Astrophysics Data System (ADS)

    Gonzalez-Piqueras, Jose; Calera, Alfonso; Gilabert, Maria A.; Cuesta, Andres; De la Cruz Tercero, Fernando

    2004-02-01

    A linear relationship between NDVI and basal crop coefficient (Kcb) allows to compute the spectral crop coefficient (Krcb). Due to the influence of soil variations varying surface humidity on NDVI, five soil optimized indices have been used to obtain a linear relationship normalized for soil background effect (SAVI, OSAVI, TSAVI, MSAVI and GESAVI). Data used on this work have been obtained from a field campaign for corn in the area of Barrax, Spain), describing crop growth stages with green fraction cover (GFC), and leaf area index (LAI). SAVI with optimized factor L set to 0.5 is a good estimator of Krcb from sparse to dense vegetation, nevertheless the soil line based index ( GESAVI) due to a wider range of variation are more sensitive to leaf variations at high levels of vegetation amount. Spectral crop coefficients obtained from SAVI and soil line based GESAVI are sensitive to crop hazards by weather anomalies and estimates in real time the basal crop coefficients to estimate the amount of water removed by the crop from the active root zone.

  14. Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

    NASA Astrophysics Data System (ADS)

    Sawant, S. A.; Chakraborty, M.; Suradhaniwar, S.; Adinarayana, J.; Durbha, S. S.

    2016-06-01

    Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (http://earthexplorer.usgs.gov/). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system

  15. Improving Spectral Crop Coefficient Approach with Raw Image Digital Count Data to Estimate Crop Water Use

    NASA Astrophysics Data System (ADS)

    Shafian, S.; Maas, S. J.; Rajan, N.

    2014-12-01

    Water resources and agricultural applications require knowledge of crop water use (CWU) over a range of spatial and temporal scales. Due to the spatial density of meteorological stations, the resolution of CWU estimates based on these data is fairly coarse and not particularly suitable or reliable for water resources planning, irrigation scheduling and decision making. Various methods have been developed for quantifying CWU of agricultural crops. In this study, an improved version of the spectral crop coefficient which includes the effects of stomatal closure is applied. Raw digital count (DC) data in the red, near-infrared, and thermal infrared (TIR) spectral bands of Landsat-7 and Landsat-8 imaging sensors are used to construct the TIR-ground cover (GC) pixel data distribution and estimate the effects of stomatal closure. CWU is then estimated by combining results of the spectral crop coefficient approach and the stomatal closer effect. To test this approach, evapotranspiration was measured in 5 agricultural fields in the semi-arid Texas High Plains during the 2013 and 2014 growing seasons and compared to corresponding estimated values of CWU determined using this approach. The results showed that the estimated CWU from this approach was strongly correlated (R2 = 0.79) with observed evapotranspiration. In addition, the results showed that considering the stomatal closer effect in the proposed approach can improve the accuracy of the spectral crop coefficient method. These results suggest that the proposed approach is suitable for operational estimation of evapotranspiration and irrigation scheduling where irrigation is used to replace the daily CWU of a crop.

  16. Estimating cropland NPP using national crop inventory and MODIS derived crop specific parameters

    NASA Astrophysics Data System (ADS)

    Bandaru, V.; West, T. O.; Ricciuto, D. M.

    2011-12-01

    Estimates of cropland net primary production (NPP) are needed as input for estimates of carbon flux and carbon stock changes. Cropland NPP is currently estimated using terrestrial ecosystem models, satellite remote sensing, or inventory data. All three of these methods have benefits and problems. Terrestrial ecosystem models are often better suited for prognostic estimates rather than diagnostic estimates. Satellite-based NPP estimates often underestimate productivity on intensely managed croplands and are also limited to a few broad crop categories. Inventory-based estimates are consistent with nationally collected data on crop yields, but they lack sub-county spatial resolution. Integrating these methods will allow for spatial resolution consistent with current land cover and land use, while also maintaining total biomass quantities recorded in national inventory data. The main objective of this study was to improve cropland NPP estimates by using a modification of the CASA NPP model with individual crop biophysical parameters partly derived from inventory data and MODIS 8day 250m EVI product. The study was conducted for corn and soybean crops in Iowa and Illinois for years 2006 and 2007. We used EVI as a linear function for fPAR, and used crop land cover data (56m spatial resolution) to extract individual crop EVI pixels. First, we separated mixed pixels of both corn and soybean that occur when MODIS 250m pixel contains more than one crop. Second, we substituted mixed EVI pixels with nearest pure pixel values of the same crop within 1km radius. To get more accurate photosynthetic active radiation (PAR), we applied the Mountain Climate Simulator (MTCLIM) algorithm with the use of temperature and precipitation data from the North American Land Data Assimilation System (NLDAS-2) to generate shortwave radiation data. Finally, county specific light use efficiency (LUE) values of each crop for years 2006 to 2007 were determined by application of mean county inventory

  17. Drought impacts and resilience on crops via evapotranspiration estimations

    NASA Astrophysics Data System (ADS)

    Timmermans, Joris; Asadollahi Dolatabad, Saeid

    2015-04-01

    Currently, the global needs for food and water is at a critical level. It has been estimated that 12.5 % of the global population suffers from malnutrition and 768 million people still do not have access to clean drinking water. This need is increasing because of population growth but also by climate change. Changes in precipitation patterns will result either in flooding or droughts. Consequently availability, usability and affordability of water is becoming challenge and efficient use of water and water management is becoming more important, particularly during severe drought events. Drought monitoring for agricultural purposes is very hard. While meteorological drought can accurately be monitored using precipitation only, estimating agricultural drought is more difficult. This is because agricultural drought is dependent on the meteorological drought, the impacts on the vegetation, and the resilience of the crops. As such not only precipitation estimates are required but also evapotranspiration at plant/plot scale. Evapotranspiration (ET) describes the amount of water evaporated from soil and vegetation. As 65% of precipitation is lost by ET, drought severity is highly linked with this variable. In drought research, the precise quantification of ET and its spatio-temporal variability is therefore essential. In this view, remote sensing based models to estimate ET, such as SEBAL and SEBS, are of high value. However the resolution of current evapotranspiration products are not good enough for monitoring the impact of the droughts on the specific crops. This limitation originates because plot scales are in general smaller than the resolution of the available satellite ET products. As such remote sensing estimates of evapotranspiration are always a combination of different land surface types and cannot be used for plant health and drought resilience studies. The goal of this research is therefore to enable adequate resolutions of daily evapotranspiration estimates

  18. Crop parameters estimation by fuzzy inference system using X-band scatterometer data

    NASA Astrophysics Data System (ADS)

    Pandey, Abhishek; Prasad, R.; Singh, V. P.; Jha, S. K.; Shukla, K. K.

    2013-03-01

    Learning fuzzy rule based systems with microwave remote sensing can lead to very useful applications in solving several problems in the field of agriculture. Fuzzy logic provides a simple way to arrive at a definite conclusion based upon imprecise, ambiguous, vague, noisy or missing input information. In the present paper, a subtractive based fuzzy inference system is introduced to estimate the potato crop parameters like biomass, leaf area index, plant height and soil moisture. Scattering coefficient for HH- and VV-polarizations were used as an input in the Fuzzy network. The plant height, biomass, and leaf area index of potato crop and soil moisture measured at its various growth stages were used as the target variables during the training and validation of the network. The estimated values of crop/soil parameters by this methodology are much closer to the experimental values. The present work confirms the estimation abilities of fuzzy subtractive clustering in potato crop parameters estimation. This technique may be useful for the other crops cultivated over regional or continental level.

  19. Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin.

    PubMed

    Siderius, Christian; Biemans, Hester; van Walsum, Paul E V; van Ierland, Ekko C; Kabat, Pavel; Hellegers, Petra J G J

    2016-01-01

    One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999-2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions.

  20. Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin.

    PubMed

    Siderius, Christian; Biemans, Hester; van Walsum, Paul E V; van Ierland, Ekko C; Kabat, Pavel; Hellegers, Petra J G J

    2016-01-01

    One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999-2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. PMID:26934389

  1. Flexible Strategies for Coping with Rainfall Variability: Seasonal Adjustments in Cropped Area in the Ganges Basin

    PubMed Central

    Siderius, Christian; Biemans, Hester; van Walsum, Paul E. V.; van Ierland, Ekko C.; Kabat, Pavel; Hellegers, Petra J. G. J.

    2016-01-01

    One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. PMID:26934389

  2. Global sensitivity of high-resolution estimates of crop water footprint

    NASA Astrophysics Data System (ADS)

    Tuninetti, Marta; Tamea, Stefania; D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

    2015-10-01

    Most of the human appropriation of freshwater resources is for agriculture. Water availability is a major constraint to mankind's ability to produce food. The notion of virtual water content (VWC), also known as crop water footprint, provides an effective tool to investigate the linkage between food and water resources as a function of climate, soil, and agricultural practices. The spatial variability in the virtual water content of crops is here explored, disentangling its dependency on climate and crop yields and assessing the sensitivity of VWC estimates to parameter variability and uncertainty. Here we calculate the virtual water content of four staple crops (i.e., wheat, rice, maize, and soybean) for the entire world developing a high-resolution (5 × 5 arc min) model, and we evaluate the VWC sensitivity to input parameters. We find that food production almost entirely depends on green water (>90%), but, when applied, irrigation makes crop production more water efficient, thus requiring less water. The spatial variability of the VWC is mostly controlled by the spatial patterns of crop yields with an average correlation coefficient of 0.83. The results of the sensitivity analysis show that wheat is most sensitive to the length of the growing period, rice to reference evapotranspiration, maize and soybean to the crop planting date. The VWC sensitivity varies not only among crops, but also across the harvested areas of the world, even at the subnational scale.

  3. A new remote sensing procedure for the estimation of crop water requirements

    NASA Astrophysics Data System (ADS)

    Spiliotopoulos, M.; Loukas, A.; Mylopoulos, N.

    2015-06-01

    The objective of this work is the development of a new approach for the estimation of water requirements for the most important crops located at Karla Watershed, central Greece. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) was used as a basis for the derivation of actual evapotranspiration (ET) and crop coefficient (ETrF) values from Landsat ETM+ imagery. MODIS imagery has been also used, and a spatial downscaling procedure is followed between the two sensors for the derivation of a new NDVI product with a spatial resolution of 30 m x 30 m. GER 1500 spectro-radiometric measurements are additionally conducted during 2012 growing season. Cotton, alfalfa, corn and sugar beets fields are utilized, based on land use maps derived from previous Landsat 7 ETM+ images. A filtering process is then applied to derive NDVI values after acquiring Landsat ETM+ based reflectance values from the GER 1500 device. ETrF vs NDVI relationships are produced and then applied to the previous satellite based downscaled product in order to finally derive a 30 m x 30 m daily ETrF map for the study area. CropWat model (FAO) is then applied, taking as an input the new crop coefficient values with a spatial resolution of 30 m x 30 m available for every crop. CropWat finally returns daily crop water requirements (mm) for every crop and the results are analyzed and discussed.

  4. Estimating crop acreage from space-simulated multispectral scanner data

    NASA Technical Reports Server (NTRS)

    Nalepka, R. F.; Hyde, P. D.

    1973-01-01

    The need for multispectral data processing methods to permit the estimation of proportions of objects and materials appearing within the instantaneous field of view of a scanning system is discussed. An algorithm developed for proportion estimation is described as well as other supporting processing techniques. Application of this algorithm to space-simulated multispectral scanner data is discussed and some results presented and compared. Results indicate that, for this data set, the true proportions of the various crops contained within this data set are with one exception more closely in agreement with the proportions determined by the proportion estimation algorithm than with the proportions determined by conventional classfication algorithm.

  5. Soil Moisture as an Estimator for Crop Yield in Germany

    NASA Astrophysics Data System (ADS)

    Peichl, Michael; Meyer, Volker; Samaniego, Luis; Thober, Stephan

    2015-04-01

    Annual crop yield depends on various factors such as soil properties, management decisions, and meteorological conditions. Unfavorable weather conditions, e.g. droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany. Predicting crop yields allows to mitigate negative effects of weather extremes which are assumed to occur more often in the future due to climate change. A standard approach in economics is to predict the impact of climate change on agriculture as a function of temperature and precipitation. This approach has been developed further using concepts like growing degree days. Other econometric models use nonlinear functions of heat or vapor pressure deficit. However, none of these approaches uses soil moisture to predict crop yield. We hypothesize that soil moisture is a better indicator to explain stress on plant growth than estimations based on precipitation and temperature. This is the case because the latter variables do not explicitly account for the available water content in the root zone, which is the primary source of water supply for plant growth. In this study, a reduced form panel approach is applied to estimate a multivariate econometric production function for the years 1999 to 2010. Annual crop yield data of various crops on the administrative district level serve as depending variables. The explanatory variable of major interest is the Soil Moisture Index (SMI), which quantifies anomalies in root zone soil moisture. The SMI is computed by the mesoscale Hydrological Model (mHM, www.ufz.de/mhm). The index represents the monthly soil water quantile at a 4 km2 grid resolution covering entire Germany. A reduced model approach is suitable because the SMI is the result of a stochastic weather process and therefore can be considered exogenous. For the ease of interpretation a linear functionality is preferred. Meteorological

  6. Impacts of spatial heterogeneity on crop area mapping in Canada using MODIS data

    NASA Astrophysics Data System (ADS)

    Chen, Yaoliang; Song, Xiaodong; Wang, Shusen; Huang, Jingfeng; Mansaray, Lamin R.

    2016-09-01

    Accurately mapping crop area using coarse spatial resolution remote sensing imageries is challenging due to the existence of various spatial heterogeneities. The objective of this study is to analyze the accuracy of crop classification and area estimation affected by spatial heterogeneities, especially for sample impurity and landscape heterogeneity. The Normalized Difference Vegetation Index (NDVI) time series calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) MOD09Q1 8-day composites and the derived phenology metrics were used to classify crop areas over Manitoba, Canada. The Classification and Regression Trees (CART) approach was applied in the classification. The Agriculture and Agri-Food Canada (AAFC) Land Cover Dataset with 30 m spatial resolution was used as the base map to determine the study regions and training and validation samples. The results allowed to conclude that: (1) the classification accuracy of MODIS imagery is sensitive to both sample impurity and landscape heterogeneity. Purity limitations in samples can have a large impact on the classification accuracy. Regions with more homogenous pixels are more likely to be accurately classified and vice versa; (2) the crop area estimation error is less sensitive to sample impurity. It is not only determined by the purity of training samples but also by the actual purity condition of the crop type. The purest training sample group does not correspond well with the lowest error; (3) the impact of configurational heterogeneity on the area estimation is more significant than that of the compositional heterogeneity. Overall, both the sample impurity and landscape heterogeneities can largely affect the classification accuracy while only configurational heterogeneity has significant influence on crop area estimation.

  7. Development of Crop Yield Estimation Method by Applying Seasonal Climate Prediction in Asia-Pacific Region

    NASA Astrophysics Data System (ADS)

    Shin, Y.; Lee, E.

    2015-12-01

    Under the influence of recent climate change, abnormal weather condition such as floods and droughts has issued frequently all over the world. The occurrence of abnormal weather in major crop production areas leads to soaring world grain prices because it influence the reduction of crop yield. Development of crop yield estimation method is important means to accommodate the global food crisis caused by abnormal weather. However, due to problems with the reliability of the seasonal climate prediction, application research on agricultural productivity has not been much progress yet. In this study, it is an object to develop long-term crop yield estimation method in major crop production countries worldwide using multi seasonal climate prediction data collected by APEC Climate Center. There are 6-month lead seasonal predictions produced by six state-of-the-art global coupled ocean-atmosphere models(MSC_CANCM3, MSC_CANCM4, NASA, NCEP, PNU, POAMA). First of all, we produce a customized climate data through temporal and spatial downscaling methods for use as a climatic input data to the global scale crop model. Next, we evaluate the uncertainty of climate prediction by applying multi seasonal climate prediction in the crop model. Because rice is the most important staple food crop in the Asia-Pacific region, we assess the reliability of the rice yields using seasonal climate prediction for main rice production countries. RMSE(Root Mean Squire Error) and TCC(Temporal Correlation Coefficient) analysis is performed in Asia-Pacific countries, major 14 rice production countries, to evaluate the reliability of the rice yield according to the climate prediction models. We compare the rice yield data obtained from FAOSTAT and estimated using the seasonal climate prediction data in Asia-Pacific countries. In addition, we show that the reliability of seasonal climate prediction according to the climate models in Asia-Pacific countries where rice cultivation is being carried out.

  8. Higher U.S. Crop Prices Trigger Little Area Expansion so Marginal Land for Biofuel Crops Is Limited

    SciTech Connect

    Swinton, S.; Babcock, Bruce; James, Laura; Bandaru, Varaprasad

    2011-06-12

    By expanding energy biomass production on marginal lands that are not currently used for crops, food price increases and indirect climate change effects can be mitigated. Studies of the availability of marginal lands for dedicated bioenergy crops have focused on biophysical land traits, ignoring the human role in decisions to convert marginal land to bioenergy crops. Recent history offers insights about farmer willingness to put non-crop land into crop production. The 2006-09 leap in field crop prices and the attendant 64% gain in typical profitability led to only a 2% increase in crop planted area, mostly in the prairie states

  9. Estimating maize grain yield from crop biophysical parameters using remote sensing

    NASA Astrophysics Data System (ADS)

    Guindin-Garcia, Noemi

    The overall objective of this investigation was to develop a robust technique to predict maize (Zea mays L.) grain yield that could be applied at a regional level using remote sensing with or without a simple crop growth simulation model. This study evaluated capabilities and limitations of the Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Index 250-m and MODIS surface reflectance 500-m products to track and retrieve information over maize fields. Results demonstrated the feasibility of using MODIS data to estimate maize green leaf area index (LAIg). Estimates of maize LAIg obtained from Wide Dynamic Range Vegetation Index using data retrieved from MODIS 250-m products (e.g. MOD13Q1) can be incorporated in crop simulation models to improve LAIg simulations by the Muchow-Sinclair-Bennet (MSB) model reducing the RMSE of LAIg simulations for all years of study under irrigation. However, more accurate estimates of LAIg did not necessarily imply better final yield (FY) predictions in the MSB maize model. The approach of incorporating better LAIg estimates into crop simulation models may not offer a panacea for problem solving; this approach is limited in its ability to simulate other factors influencing crop yields. On the other hand, the approach of relating key crop biophysical parameters at the optimum stage with maize grain final yields is a robust technique to early FY estimation over large areas. Results suggest that estimates of LAI g obtained during the mid-grain filling period can used to detect variability of maize grain yield and this technique offers a rapid and accurate (RMSE < 900 kg ha-1) method to detect FY at county level using MODIS 250-m products.

  10. Evaluation of the use of remote-sensing data to identify crop types and estimate irrigated acreage, Uvalde and Medina counties, Texas, 1989

    USGS Publications Warehouse

    Raymond, L.H.; Nalley, G.M.; Rettman, P.L.

    1992-01-01

    Results were verified using crop acreages reported by the U.S. Department of Agriculture, Agricultural Stabilization and Conservation Service (ASCS). The total areas for all irrigated crops estimated using remote-sensing data were about 8 percent higher for Uvalde County and about 4 percent higher for Medina County than the areas reported by the ASCS. Irrigated-crop areas subsequently were multiplied by the respective duties of water to calculate the total quantity of water pumped from the aquifer for irrigation. Pumpage did not differ for the two estimates of crop areas for Uvalde County and differed by about 3 percent for Medina County.

  11. Asia Rice Crop Estimation and Monitoring (Asia-RiCE) for GEOGLAM

    NASA Astrophysics Data System (ADS)

    Oyoshi, K.; Tomiyama, N.; Okumura, T.; Sobue, S.

    2013-12-01

    Food security is a critical issue for the international community because of rapid population and economic growth, and climate change. In June 2011, the meeting of G20 agriculture ministers was held to discuss food security and food price volatility, and they agreed on an 'Action Plan on Food Price Volatility and Agriculture'. This plan includes a GEO Global Agricultural Monitoring (GEOGLAM) initiative. The aim of GEOGLAM is to reinforce the international community's ability to produce and disseminate relevant, timely, and accurate forecasts of agricultural production on regional, national, and global scales by utilizing remote sensing technology. GEOGLAM focused on four major grain crops, wheat, maize, soybeans and rice. In particular, Asian countries are responsible for approximately 90% of the world rice production and consumption, rice is the most significant cereal crop in Asian region. Hence, Asian space and agricultural agencies with an interest in the development of rice crop monitoring technology launched an Asia-Rice Crop Estimation & Monitoring (Asia-RiCE) component for the GEOGLAM initiative. In Asian region, rice is mainly cultivated in rainy season, and a large amount of cloud limits rice crop monitoring with optical sensors. But, Synthetic Aperture RADAR (SAR) is all-weather sensor and can observe land surface even if the area is covered by cloud. Therefore, SAR technology would be powerful tool to monitor rice crop in Asian region. Asia-RiCE team required mainly SAR observation data including ALOS-2, RISAT-1, Sentinel-1 and RADARSAT, TerraSAR-X, COSMO-SkyMed for Asia-RiCE GEOGLAM Phase 1 implementation (2013-2015) to the Committee on Earth Observations (CEOS) in the GEOGLAM-CEOS Global Agricultural Monitoring Co-community Meeting held in June 2013. And also, rice crop has complicated cropping systems such as rein-fed or irrigated cultivation, single, double or sometimes triple cropping. In addition, each agricultural field is smaller than that of

  12. Health Service Areas (HSAs) - Small Area Estimates

    Cancer.gov

    Health Service Areas (HSAs) are a compromise between the 3000 counties and the 50 states. An HSA may be thought of as an area that is relatively self-contained with respect to hospital care and may cross over state boundries.

  13. Crop-specific seasonal estimates of irrigation water demand in South Asia

    NASA Astrophysics Data System (ADS)

    Biemans, H.; Siderius, C.; Mishra, A.; Ahmad, B.

    2015-08-01

    Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight in these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation water demand resulting from the typical practice of multiple-cropping in South Asia was accounted for by introducing double-cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest subnational statistics of India, Pakistan, Bangladesh and Nepal. The representation of seasonal land use and more accurate cropping periods lead to lower estimates of irrigation water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation water demand differs sharply between seasons and regions; in Pakistan, winter (Rabi) and summer (Kharif) irrigation demands are almost equal, whereas in Bangladesh the Rabi demand is ~ 100 times higher. Moreover, the relative importance of irrigation supply vs. rain decreases sharply from west to east. Given the size and importance of South Asia, improved regional estimates of food production and its irrigation water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple-cropping and monsoon-dependent planting dates should not be ignored.

  14. Crop-specific seasonal estimates of irrigation-water demand in South Asia

    NASA Astrophysics Data System (ADS)

    Biemans, Hester; Siderius, Christian; Mishra, Ashok; Ahmad, Bashir

    2016-05-01

    Especially in the Himalayan headwaters of the main rivers in South Asia, shifts in runoff are expected as a result of a rapidly changing climate. In recent years, our insight into these shifts and their impact on water availability has increased. However, a similar detailed understanding of the seasonal pattern in water demand is surprisingly absent. This hampers a proper assessment of water stress and ways to cope and adapt. In this study, the seasonal pattern of irrigation-water demand resulting from the typical practice of multiple cropping in South Asia was accounted for by introducing double cropping with monsoon-dependent planting dates in a hydrology and vegetation model. Crop yields were calibrated to the latest state-level statistics of India, Pakistan, Bangladesh and Nepal. The improvements in seasonal land use and cropping periods lead to lower estimates of irrigation-water demand compared to previous model-based studies, despite the net irrigated area being higher. Crop irrigation-water demand differs sharply between seasons and regions; in Pakistan, winter (rabi) and monsoon summer (kharif) irrigation demands are almost equal, whereas in Bangladesh the rabi demand is ~ 100 times higher. Moreover, the relative importance of irrigation supply versus rain decreases sharply from west to east. Given the size and importance of South Asia improved regional estimates of food production and its irrigation-water demand will also affect global estimates. In models used for global water resources and food-security assessments, processes like multiple cropping and monsoon-dependent planting dates should not be ignored.

  15. GPP estimates in a biodiesel crop using MERIS products

    NASA Astrophysics Data System (ADS)

    Sánchez, M. L.; Pardo, N.; Pérez, I.; García, M. A.; Paredes, V.

    2012-04-01

    Greenhouse gas emissions in Spain in 2008-2009 were 34.3 % higher than the base-year level, significantly above the burden-sharing target of 15 % for the period 2008-2012. Based on this result, our country will need to make a major effort to meet the committed target on time using domestic measures as well as others foreseen in the Kyoto Protocol, such as LULUFC activities. In this framework, agrofuels, in other words biofuels produced by crops that contain high amounts of vegetable oil such as sorghum, sunflower, rape seed and jatropha, appear to be an interesting mitigation alternative. Bearing in mind the meteorological conditions in Spain, sunflower and rape seed in particular are considered the most viable crops. Sunflower cultivated surface in Spain has remained fairly constant in recent years, in contrast to rapeseed crop surface which, although still scarce, has followed an increasing trend. In order to assess rape seed ability as a CO2 sink as well as to describe GPP dynamic evolution, we installed an eddy correlation station in an agricultural plot of the Spanish plateau. Measurements at the plot consisted of 30-min NEE flux measurements (using a LI-7500 and a METEK USA-1 sonic anemometer) as well as other common meteorological variables. Measurements were performed from March to October. This paper presents the results of the GPP 8-d estimated values using a Light Use Efficiency Model, LUE. Input data for the LUE model were the FPAR 8-d products supplied by MERIS, the PAR in situ measurements, and a scalar f varying, between 0 and 1, to take into account the reduction of the maximum PAR conversion efficiency, ɛ0, under limiting environmental conditions. The f values were assumed to be dependent on air temperature and the evaporative fraction, EF, which was considered as a proxy of soil moisture. ɛ0, a key parameter, which depends on biome types, was derived through the results of a linear regression fit between the GPP 8-d eddy covariance composites

  16. General multiyear aggregation technology: Methodology and software documentation. [estimating seasonal crop acreage proportions

    NASA Technical Reports Server (NTRS)

    Baker, T. C. (Principal Investigator)

    1982-01-01

    A general methodology is presented for estimating a stratum's at-harvest crop acreage proportion for a given crop year (target year) from the crop's estimated acreage proportion for sample segments from within the stratum. Sample segments from crop years other than the target year are (usually) required for use in conjunction with those from the target year. In addition, the stratum's (identifiable) crop acreage proportion may be estimated for times other than at-harvest in some situations. A by-product of the procedure is a methodology for estimating the change in the stratum's at-harvest crop acreage proportion from crop year to crop year. An implementation of the proposed procedure as a statistical analysis system routine using the system's matrix language module, PROC MATRIX, is described and documented. Three examples illustrating use of the methodology and algorithm are provided.

  17. Are satellite based rainfall estimates accurate enough for crop modelling under Sahelian climate?

    NASA Astrophysics Data System (ADS)

    Ramarohetra, J.; Sultan, B.

    2012-04-01

    Agriculture is considered as the most climate dependant human activity. In West Africa and especially in the sudano-sahelian zone, rain-fed agriculture - that represents 93% of cultivated areas and is the means of support of 70% of the active population - is highly vulnerable to precipitation variability. To better understand and anticipate climate impacts on agriculture, crop models - that estimate crop yield from climate information (e.g rainfall, temperature, insolation, humidity) - have been developed. These crop models are useful (i) in ex ante analysis to quantify the impact of different strategies implementation - crop management (e.g. choice of varieties, sowing date), crop insurance or medium-range weather forecast - on yields, (ii) for early warning systems and to (iii) assess future food security. Yet, the successful application of these models depends on the accuracy of their climatic drivers. In the sudano-sahelian zone , the quality of precipitation estimations is then a key factor to understand and anticipate climate impacts on agriculture via crop modelling and yield estimations. Different kinds of precipitation estimations can be used. Ground measurements have long-time series but an insufficient network density, a large proportion of missing values, delay in reporting time, and they have limited availability. An answer to these shortcomings may lie in the field of remote sensing that provides satellite-based precipitation estimations. However, satellite-based rainfall estimates (SRFE) are not a direct measurement but rather an estimation of precipitation. Used as an input for crop models, it determines the performance of the simulated yield, hence SRFE require validation. The SARRAH crop model is used to model three different varieties of pearl millet (HKP, MTDO, Souna3) in a square degree centred on 13.5°N and 2.5°E, in Niger. Eight satellite-based rainfall daily products (PERSIANN, CMORPH, TRMM 3b42-RT, GSMAP MKV+, GPCP, TRMM 3b42v6, RFEv2 and

  18. Spring Small Grains Area Estimation

    NASA Technical Reports Server (NTRS)

    Palmer, W. F.; Mohler, R. J.

    1986-01-01

    SSG3 automatically estimates acreage of spring small grains from Landsat data. Report describes development and testing of a computerized technique for using Landsat multispectral scanner (MSS) data to estimate acreage of spring small grains (wheat, barley, and oats). Application of technique to analysis of four years of data from United States and Canada yielded estimates of accuracy comparable to those obtained through procedures that rely on trained analysis.

  19. Crop Acreage Estimation: Landsat TM and Resourcesat-1 AWiFS Sensor Assessment of the Mississippi River Delta, 2005

    NASA Technical Reports Server (NTRS)

    Boryan, Claire; Johnson, Dave; Craig, Mike; Seffrin, Bob; Mueller, RIck

    2007-01-01

    AWiFs data are appropriate for crop acreage estimation over large, spectrally homogenous, crop areas such as the Mid-West, the Delta and the Northern Great Plains. Regression and Kappa statistics for soybean, corn, cotton, rice and sorghum produced using both the Landsat TM and AWiFS data are very similar. AWiFS data appear to be a suitable alternative or supplement to Landsat TM data for production of NASS'Cropland Data Layer product.

  20. SACRA - a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

    NASA Astrophysics Data System (ADS)

    Kotsuki, S.; Tanaka, K.

    2015-11-01

    To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004-2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most of the areas. A major disadvantage of our method is that the mixture of several crops in a grid is not considered in SACRA. The assumption of one dominant crop in each grid is a major source of discrepancy in crop calendars between SACRA and other products. The disadvantages of our approach may be reduced with future improvements based on finer satellite sensors and crop-type classification studies to consider several dominant crops in each grid. The comparison of the CC also demonstrates that identification of wheat type (sowing in

  1. Regression model estimation of early season crop proportions: North Dakota, some preliminary results

    NASA Technical Reports Server (NTRS)

    Lin, K. K. (Principal Investigator)

    1982-01-01

    To estimate crop proportions early in the season, an approach is proposed based on: use of a regression-based prediction equation to obtain an a priori estimate for specific major crop groups; modification of this estimate using current-year LANDSAT and weather data; and a breakdown of the major crop groups into specific crops by regression models. Results from the development and evaluation of appropriate regression models for the first portion of the proposed approach are presented. The results show that the model predicts 1980 crop proportions very well at both county and crop reporting district levels. In terms of planted acreage, the model underpredicted 9.1 percent of the 1980 published data on planted acreage at the county level. It predicted almost exactly the 1980 published data on planted acreage at the crop reporting district level and overpredicted the planted acreage by just 0.92 percent.

  2. Estimating national crop yield potential and the relevance of weather data sources

    NASA Astrophysics Data System (ADS)

    Van Wart, Justin

    2011-12-01

    To determine where, when, and how to increase yields, researchers often analyze the yield gap (Yg), the difference between actual current farm yields and crop yield potential. Crop yield potential (Yp) is the yield of a crop cultivar grown under specific management limited only by temperature and solar radiation and also by precipitation for water limited yield potential (Yw). Yp and Yw are critical components of Yg estimations, but are very difficult to quantify, especially at larger scales because management data and especially daily weather data are scarce. A protocol was developed to estimate Yp and Yw at national scales using site-specific weather, soils and management data. Protocol procedures and inputs were evaluated to determine how to improve accuracy of Yp, Yw and Yg estimates. The protocol was also used to evaluate raw, site-specific and gridded weather database sources for use in simulations of Yp or Yw. The protocol was applied to estimate crop Yp in US irrigated maize and Chinese irrigated rice and Yw in US rainfed maize and German rainfed wheat. These crops and countries account for >20% of global cereal production. The results have significant implications for past and future studies of Yp, Yw and Yg. Accuracy of national long-term average Yp and Yw estimates was significantly improved if (i) > 7 years of simulations were performed for irrigated and > 15 years for rainfed sites, (ii) > 40% of nationally harvested area was within 100 km of all simulation sites, (iii) observed weather data coupled with satellite derived solar radiation data were used in simulations, and (iv) planting and harvesting dates were specified within +/- 7 days of farmers actual practices. These are much higher standards than have been applied in national estimates of Yp and Yw and this protocol is a substantial step in making such estimates more transparent, robust, and straightforward. Finally, this protocol may be a useful tool for understanding yield trends and directing

  3. Large Area Crop Inventory Experiment (LACIE). An overview of the Large Area Crop Inventory Experiment and the outlook for a satellite crop inventory. [Great Plains Corridor (North America), Canada, U.S.S.R., Brazil, China, India, and Australia

    NASA Technical Reports Server (NTRS)

    Erb, R. B. (Principal Investigator)

    1979-01-01

    The author has identified the following significant results. The most important LACIE finding was that the technology worked very well in estimating wheat production in important geographic locations. Based on working through the many successes and shortcomings of LACIE, it can be stated with confidence that: (1) the current technology can successfully monitor what production in regions having similar characteristics to those of the U.S.S.R. wheat areas and the U.S. hard red winter wheat areas; (2) with additional applied research, significant improvements in capabilities to monitor wheat in these and other important production regions can be expected in the near future; (3) the remote sensing and weather effects modeling technology approached used by LACIE is generally applicable to other major crops and crop-producing regions of the world; and (4) with suitable effort, this technology can now advance rapidly and could be widespread use in the late 1980's.

  4. Use of thermal and visible imagery for estimating crop water status of irrigated grapevine.

    PubMed

    Möller, M; Alchanatis, V; Cohen, Y; Meron, M; Tsipris, J; Naor, A; Ostrovsky, V; Sprintsin, M; Cohen, S

    2007-01-01

    Achieving high quality wine grapes depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. This study investigates the use of thermal imaging for monitoring water stress. Experiments were conducted on a wine-grape (Vitis vinifera cv. Merlot) vineyard in northern Israel. Irrigation treatments included mild, moderate, and severe stress. Thermal and visible (RGB) images of the crop were taken on four days at midday with a FLIR thermal imaging system and a digital camera, respectively, both mounted on a truck-crane 15 m above the canopy. Aluminium crosses were used to match visible and thermal images in post-processing and an artificial wet surface was used to estimate the reference wet temperature (T(wet)). Monitored crop parameters included stem water potential (Psi(stem)), leaf conductance (g(L)), and leaf area index (LAI). Meteorological parameters were measured at 2 m height. CWSI was highly correlated with g(L) and moderately correlated with Psi(stem). The CWSI-g(L) relationship was very stable throughout the season, but for that of CWSI-Psi(stem) both intercept and slope varied considerably. The latter presumably reflects the non-direct nature of the physiological relationship between CWSI and Psi(stem). The highest R(2) for the CWSI to g(L) relationship, 0.91 (n=12), was obtained when CWSI was computed using temperatures from the centre of the canopy, T(wet) from the artificial wet surface, and reference dry temperature from air temperature plus 5 degrees C. Using T(wet) calculated from the inverted Penman-Monteith equation and estimated from an artificially wetted part of the canopy also yielded crop water-stress estimates highly correlated with g(L) (R(2)=0.89 and 0.82, respectively), while a crop water-stress index using 'theoretical' reference temperatures computed from climate data showed significant deviations in the late season. Parameter variability and robustness of the different CWSI estimates

  5. Use of thermal and visible imagery for estimating crop water status of irrigated grapevine.

    PubMed

    Möller, M; Alchanatis, V; Cohen, Y; Meron, M; Tsipris, J; Naor, A; Ostrovsky, V; Sprintsin, M; Cohen, S

    2007-01-01

    Achieving high quality wine grapes depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. This study investigates the use of thermal imaging for monitoring water stress. Experiments were conducted on a wine-grape (Vitis vinifera cv. Merlot) vineyard in northern Israel. Irrigation treatments included mild, moderate, and severe stress. Thermal and visible (RGB) images of the crop were taken on four days at midday with a FLIR thermal imaging system and a digital camera, respectively, both mounted on a truck-crane 15 m above the canopy. Aluminium crosses were used to match visible and thermal images in post-processing and an artificial wet surface was used to estimate the reference wet temperature (T(wet)). Monitored crop parameters included stem water potential (Psi(stem)), leaf conductance (g(L)), and leaf area index (LAI). Meteorological parameters were measured at 2 m height. CWSI was highly correlated with g(L) and moderately correlated with Psi(stem). The CWSI-g(L) relationship was very stable throughout the season, but for that of CWSI-Psi(stem) both intercept and slope varied considerably. The latter presumably reflects the non-direct nature of the physiological relationship between CWSI and Psi(stem). The highest R(2) for the CWSI to g(L) relationship, 0.91 (n=12), was obtained when CWSI was computed using temperatures from the centre of the canopy, T(wet) from the artificial wet surface, and reference dry temperature from air temperature plus 5 degrees C. Using T(wet) calculated from the inverted Penman-Monteith equation and estimated from an artificially wetted part of the canopy also yielded crop water-stress estimates highly correlated with g(L) (R(2)=0.89 and 0.82, respectively), while a crop water-stress index using 'theoretical' reference temperatures computed from climate data showed significant deviations in the late season. Parameter variability and robustness of the different CWSI estimates

  6. Estimated winter wheat yield from crop growth predicted by LANDSAT

    NASA Technical Reports Server (NTRS)

    Kanemasu, E. T.

    1977-01-01

    An evapotranspiration and growth model for winter wheat is reported. The inputs are daily solar radiation, maximum temperature, minimum temperature, precipitation/irrigation and leaf area index. The meteorological data were obtained from National Weather Service while LAI was obtained from LANDSAT multispectral scanner. The output provides daily estimates of potential evapotranspiration, transpiration, evaporation, soil moisture (50 cm depth), percentage depletion, net photosynthesis and dry matter production. Winter wheat yields are correlated with transpiration and dry matter accumulation.

  7. Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models

    PubMed Central

    Trnka, Miroslav; Eitzinger, Josef; Kapler, Pavel; Dubrovský, Martin; Semerádová, Daniela; Žalud, Zden ěk; Formayer, Herbert

    2007-01-01

    The results of previous studies have suggested that estimated daily global radiation (RG) values contain an error that could compromise the precision of subsequent crop model applications. The following study presents a detailed site and spatial analysis of the RG error propagation in CERES and WOFOST crop growth models in Central European climate conditions. The research was conducted i) at the eight individual sites in Austria and the Czech Republic where measured daily RG values were available as a reference, with seven methods for RG estimation being tested, and ii) for the agricultural areas of the Czech Republic using daily data from 52 weather stations, with five RG estimation methods. In the latter case the RG values estimated from the hours of sunshine using the Ångström-Prescott formula were used as the standard method because of the lack of measured RG data. At the site level we found that even the use of methods based on hours of sunshine, which showed the lowest bias in RG estimates, led to a significant distortion of the key crop model outputs. When the Ångström-Prescott method was used to estimate RG, for example, deviations greater than ±10 per cent in winter wheat and spring barley yields were noted in 5 to 6 per cent of cases. The precision of the yield estimates and other crop model outputs was lower when RG estimates based on the diurnal temperature range and cloud cover were used (mean bias error 2.0 to 4.1 per cent). The methods for estimating RG from the diurnal temperature range produced a wheat yield bias of more than 25 per cent in 12 to 16 per cent of the seasons. Such uncertainty in the crop model outputs makes the reliability of any seasonal yield forecasts or climate change impact assessments questionable if they are based on this type of data. The spatial assessment of the RG data uncertainty propagation over the winter wheat yields also revealed significant differences within the study area. We found that RG estimates based on

  8. Estimating winter wheat phenological parameters: Implications for crop modeling

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop parameters, such as the timing of developmental events, are critical for accurate simulation results in crop simulation models, yet uncertainty often exists in determining the parameters. Factors contributing to the uncertainty include: a) sources of variation within a plant (i.e., within diffe...

  9. Utility of multi temporal satellite images for crop water requirements estimation and irrigation management in the Jordan Valley

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Identifying the spatial and temporal distribution of crop water requirements is a key for successful management of water resources in the dry areas. Climatic data were obtained from three automated weather stations to estimate reference evapotranspiration (ETO) in the Jordan Valley according to the...

  10. Could an abandoned mercury mine area be cropped?

    PubMed

    Rocio, Millán; Elvira, Esteban; Pilar, Zornoza; María-José, Sierra

    2013-08-01

    The Almadén area (Spain) is known for its high natural mercury background as well as for the anthropogenic impact due to mining activities. After the end of these activities, appropriate alternative use of the soil has to be found, and agricultural activities stand out as an environmentally-friendly and potentially profitable alternative, giving to the soil a sustainable use without risks for human or animal health according to current legislation. Experiments performed at different scales (involving hydroponics, growth in pots and lysimeters) allow recommendations to be made regarding the adequacy of cultivation of different crops for animal or human consumption before they are sown in the field. Regarding crops for animal feeding, mercury accumulation in vegetative organs represents a higher potential risk for animals. Nevertheless, seeds and fruits can be used, both for human and animal consumption. Finally, this work will lead the way to obtain a scientific basis for elaborating a list of recommendations on sustainable and safe alternative land use, according to current international legislation.

  11. SEBAL Model Using to Estimate Irrigation Water Efficiency & Water Requirement of Alfalfa Crop

    NASA Astrophysics Data System (ADS)

    Zeyliger, Anatoly; Ermolaeva, Olga

    2013-04-01

    The sustainability of irrigation is a complex and comprehensive undertaking, requiring an attention to much more than hydraulics, chemistry, and agronomy. A special combination of human, environmental, and economic factors exists in each irrigated region and must be recognized and evaluated. A way to evaluate the efficiency of irrigation water use for crop production is to consider the so-called crop-water production functions, which express the relation between the yield of a crop and the quantity of water applied to it or consumed by it. The term has been used in a somewhat ambiguous way. Some authors have defined the Crop-Water Production Functions between yield and the total amount of water applied, whereas others have defined it as a relation between yield and seasonal evapotranspiration (ET). In case of high efficiency of irrigation water use the volume of water applied is less than the potential evapotranspiration (PET), then - assuming no significant change of soil moisture storage from beginning of the growing season to its end-the volume of water may be roughly equal to ET. In other case of low efficiency of irrigation water use the volume of water applied exceeds PET, then the excess of volume of water applied over PET must go to either augmenting soil moisture storage (end-of-season moisture being greater than start-of-season soil moisture) or to runoff or/and deep percolation beyond the root zone. In presented contribution some results of a case study of estimation of biomass and leaf area index (LAI) for irrigated alfalfa by SEBAL algorithm will be discussed. The field study was conducted with aim to compare ground biomass of alfalfa at some irrigated fields (provided by agricultural farm) at Saratov and Volgograd Regions of Russia. The study was conducted during vegetation period of 2012 from April till September. All the operations from importing the data to calculation of the output data were carried by eLEAF company and uploaded in Fieldlook web

  12. Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products.

    PubMed

    Li, Jing; Bo, Yu; Xie, Shaodong

    2016-06-01

    With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°×0.25° and a temporal resolution of 1month was established based on the moderate resolution imaging spectroradiometer (MODIS) Thermal Anomalies/Fire Daily Level3 Global Product (MOD/MYD14A1). Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO2, CO, CH4, nonmethane volatile organic compounds (NMVOCs), N2O, NOx, NH3, SO2, fine particles (PM2.5), organic carbon (OC), and black carbon (BC) were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43, 1.09, 0.34, and 0.06Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June (37%). Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N2O to a high of within ±169% for NH3.

  13. Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products.

    PubMed

    Li, Jing; Bo, Yu; Xie, Shaodong

    2016-06-01

    With the objective of reducing the large uncertainties in the estimations of emissions from crop residue open burning, an improved method for establishing emission inventories of crop residue open burning at a high spatial resolution of 0.25°×0.25° and a temporal resolution of 1month was established based on the moderate resolution imaging spectroradiometer (MODIS) Thermal Anomalies/Fire Daily Level3 Global Product (MOD/MYD14A1). Agriculture mechanization ratios and regional crop-specific grain-to-straw ratios were introduced to improve the accuracy of related activity data. Locally observed emission factors were used to calculate the primary pollutant emissions. MODIS satellite data were modified by combining them with county-level agricultural statistical data, which reduced the influence of missing fire counts caused by their small size and cloud cover. The annual emissions of CO2, CO, CH4, nonmethane volatile organic compounds (NMVOCs), N2O, NOx, NH3, SO2, fine particles (PM2.5), organic carbon (OC), and black carbon (BC) were 150.40, 6.70, 0.51, 0.88, 0.01, 0.13, 0.07, 0.43, 1.09, 0.34, and 0.06Tg, respectively, in 2012. Crop residue open burning emissions displayed typical seasonal and spatial variation. The highest emission regions were the Yellow-Huai River and Yangtse-Huai River areas, and the monthly emissions were highest in June (37%). Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of within ±126% for N2O to a high of within ±169% for NH3. PMID:27266312

  14. Estimating riparian and agricultural evapotranspiration by reference crop evapotranspiration and MODIS Enhanced Vegetation Index

    USGS Publications Warehouse

    Nagler, Pamela L.; Glenn, Edward P.; Nguyen, Uyen; Scott, Russell; Doody, Tania

    2013-01-01

    Dryland river basins frequently support both irrigated agriculture and riparian vegetation and remote sensing methods are needed to monitor water use by both crops and natural vegetation in irrigation districts. We developed an algorithm for estimating actual evapotranspiration (ETa) based on the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the EOS-1 Terra satellite and locally-derived measurements of reference crop ET (ETo). The algorithm was calibrated with five years of ETa data from three eddy covariance flux towers set in riparian plant associations on the upper San Pedro River, Arizona, supplemented with ETa data for alfalfa and cotton from the literature. The algorithm was based on an equation of the form ETa = ETo [a(1 − e−bEVI) − c], where the term (1 − e−bEVI) is derived from the Beer-Lambert Law to express light absorption by a canopy, with EVI replacing leaf area index as an estimate of the density of light-absorbing units. The resulting algorithm capably predicted ETa across riparian plants and crops (r2 = 0.73). It was then tested against water balance data for five irrigation districts and flux tower data for two riparian zones for which season-long or multi-year ETa data were available. Predictions were within 10% of measured results in each case, with a non-significant (P = 0.89) difference between mean measured and modeled ETa of 5.4% over all validation sites. Validation and calibration data sets were combined to present a final predictive equation for application across crops and riparian plant associations for monitoring individual irrigation districts or for conducting global water use assessments of mixed agricultural and riparian biomes.

  15. Estimation of crops biomass and evapotranspiration from high spatial and temporal resolutions remote sensing data

    NASA Astrophysics Data System (ADS)

    Claverie, Martin; Demarez, Valérie; Duchemin, Benoît.; Ceschia, Eric; Hagolle, Olivier; Ducrot, Danielle; Keravec, Pascal; Beziat, Pierre; Dedieu, Pierre

    2010-05-01

    Carbon and water cycles are closely related to agricultural activities. Agriculture has been indeed identified by IPCC 2007 report as one of the options to sequester carbon in soil. Concerning the water resources, their consumptions by irrigated crops are called into question in view of demographic pressure. In the prospect of an assessment of carbon production and water consumption, the use of crop models at a regional scale is a challenging issue. The recent availability of high spatial resolution (10 m) optical sensors associated to high temporal resolution (1 day) such as FORMOSAT-2 and, in the future, Venµs and SENTINEL-2 will offer new perspectives for agricultural monitoring. In this context, the objective of this work is to show how multi-temporal satellite observations acquired at high spatial resolution are useful for a regional monitoring of following crops biophysical variables: leaf area index (LAI), aboveground biomass (AGB) and evapotranspiration (ET). This study focuses on three summer crops dominant in South-West of France: maize, sunflower and soybean. A unique images data set (82 FORMOSAT-2 images over four consecutive years, 2006-2009) was acquired for this project. The experimental data set includes LAI and AGB measurements over eight agricultural fields. Two fields were intensively monitored where ET flux were measured with a 30 minutes time step using eddy correlation methods. The modelisation approach is based on FAO-56 method coupled with a vegetation functioning model based on Monteith theory: the SAFY model [5]. The model operates at a daily time step model to provide estimates of plant characteristics (LAI, AGB), soil conditions (soil water content) and water use (ET). As a key linking variable, LAI is deduced from FORMOSAT-2 reflectances images, and then introduced into the SAFY model to provide spatial and temporal estimates of these biophysical variables. Most of the SAFY parameters are crop related and have been fixed according to

  16. Estimated flows of gases and carbon within CEEF ecosystem composed of human, crops and goats

    NASA Astrophysics Data System (ADS)

    Tako, Y.; Komatsubara, O.; Honda, G.; Arai, R.; Nitta, K.

    The Closed Ecology Experiment Facilities (CEEF) can be used as a test bed for Controlled Ecological Life Support Systems (CELSS), because technologies developed for the CEEF system facilitate self-sufficient material circulation necessary for long term missions such as Lunar and Mars exploration. In the experiment conducted under closed condition in FY2003, rice and soybeans were cultivated sequentially in two chambers and a chamber, each having a cultivation area of 30 m2 and floor area of 43 m2, inside the Plantation Module with artificial lighting of the CEEF. In the chamber having a cultivation area of 60 m2 and floor area of 65 m2, inside the Plantation Module with natural and artificial lighting, peanuts and safflowers were also cultivated. Stable transplant (or seeding) and harvest of each crop were maintained during a month. Flows of CO2, O2 and carbon to and from the crops were analyzed during the stable cultivation period. Simulated works and stay in the CEEF lasting five days were conducted two times under ventilating condition in FY2003. Gas exchange of human was estimated using heart rate data collected during the experiments and correlation between gas exchange rate and heart rate. Gas exchange rate and carbon balance of female goats were determined using an open-flow measurement system with a gastight chamber. From these results, flows of gases and carbon in the CEEF were discussed.

  17. An original interpretation of the wet edge of the surface temperature-albedo space to estimate crop evapotranspiration (SEB-1S), and its validation over an irrigated area in northwestern Mexico

    NASA Astrophysics Data System (ADS)

    Merlin, O.

    2013-09-01

    The space defined by the pair surface temperature (T) and surface albedo (α), and the space defined by the pair T and fractional green vegetation cover (fvg) have been extensively used to estimate evaporative fraction (EF) from solar/thermal remote sensing data. In both space-based approaches, evapotranspiration (ET) is estimated as remotely sensed EF times the available energy. For a given data point in the T-α space or in the T-fvg space, EF is derived as the ratio of the distance separating the point from the line identified as the dry edge to the distance separating the dry edge and the line identified as the wet edge. The dry and wet edges are classically defined as the upper and lower limit of the spaces, respectively. When investigating side by side the T-α and the T-fvg spaces, one observes that the range covered by T values on the (classically determined) wet edge is different for both spaces. In addition, when extending the wet and dry lines of the T-α space, both lines cross at α ≈ 0.4 although the wet and dry edges of the T-fvg space never cross for 0 ≤ fvg < 1. In this paper, a new ET (EF) model (SEB-1S) is derived by revisiting the classical physical interpretation of the T-α space to make its wet edge consistent with that of the T-fvg space. SEB-1S is tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007-2008 agricultural season. The classical T-α space-based model is implemented as benchmark to evaluate the performance of SEB-1S. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-1S and the classical T-α space-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The ET simulated by SEB-1S is significantly more accurate and robust than that predicted by the classical T

  18. Using Biome-BGC to estimate production in annual crops - A study in Nebraska

    NASA Astrophysics Data System (ADS)

    Heinsch, F. A.; Jolly, W. M.; Kimball, J. S.; Oechel, W. C.; Verma, S. B.

    2004-12-01

    The Biome-BGC ecosystem process model (Version 4.1.2) has been used successfully in many ecosystems, but was not developed for use with agricultural crops. Therefore, program modifications are needed for use with crops, including the addition of carbon allocation to fruiting and the inclusion of springtime planting. The program has been modified and tested using both C3 (soybean) and C4 (maize) vegetation. Results from the Biome-BGC model runs were validated using AmeriFlux tower eddy CO2 flux-based estimates as well as two years of biomass and yield estimates at the University of Nebraska Agricultural Research and Development Center (ARDL) near Mead, NE. The model was also used to obtain tower site and regional estimates of NEE, GPP and NPP. Preliminary results indicate that the model works well in estimating both productivity and yield of both maize and soybean. These results are combined and scaled to a 7 x 7-km area equivalent to that of the MODIS subset (resolution = 1 km2) centered on the research farm and available from Fluxnet and the Oak Ridge National Laboratory (http://www.fluxnet.ornl.gov/fluxnet/modis.cfm). The comparisons provide a means to test the ability of the MODIS algorithms to capture seasonal variations and agricultural carbon dynamics. The results of this study will be used in the future for spatial extrapolation to scales from 1 - 20,000 km2 to evaluate relative accuracies of MODIS GPP/NPP regional data and provide estimates of the regional carbon balance for the larger 20,000 km2 area within the National Institute for Global Environmental Change (NIGEC) Great Plains and Midwestern study regions.

  19. Evaluation of the kriging method to predict 7-h seasonal mean ozone concentrations for estimating crop losses

    SciTech Connect

    Lefohn, A.S.; Knudsen, H.P.; Logan, J.A.; Simpson, J.; Bhumralkar, C.

    1987-05-01

    Using kriging, a statistical technique, the National Crop Loss Assessment Network (NCLAN) program estimated growing season 5-month (May-September) ambient 7-h mean O3 concentrations for each of the major crop growing areas of the US for 1978-1982. The O3 estimates were used to predict economic benefits anticipated by lowering O3 levels in the US. This paper reviews NCLAN's use of kriging to estimate 7-h seasonal mean O3 concentrations for crop growing regions. Although the original kriging program used by NCLAN incorrectly calculated the diagonal elements of the kriging equations, this omission did not result in significant errors in the predicted estimates. Most of the data used in estimating the 7-h seasonal values were obtained from urban areas; the use of these data tended to underestimate the 7-h seasonal O3 concentrations in rural areas. It is recommended that only O3 data that are representative of agricultural areas and have been collected under accepted quality assurance programs be used in future kriging efforts.

  20. Evaluation of the kriging method to predict 7-h seasonal mean ozone concentrations for estimating crop losses (journal version)

    SciTech Connect

    Lefohn, A.S.; Knudsen, H.P.; Logan, J.A.; Simpson, J.; Bhumralkar, C.

    1987-01-01

    Using kriging, a statistical technique, the National Crop Loss Assessment Network (NCLAN) program estimated growing season 5-month (May-September) ambient 7-h mean O/sub 3/ concentrations for each of the major crop growing areas of the United States for 1978-1982. The O/sub 3/ estimates were used to predict economic benefits anticipated by lowering O/sub 3/ levels in the United States. This paper reviews NCLAN's use of kriging to estimate 7-h seasonal mean O/sub 3/ concentrations for crop growing regions. Although the original kriging program used by NCLAN incorrectly calculated the diagonal elements of the kriging equations, this omission did not result in significant errors in the predicted estimates. Most of the data used in estimating the 7-h seasonal values were obtained from urban areas; the use of these data tended to underestimate the 7-h seasonal O/sub 3/ concentrations in rural areas. It is recommended that only O/sub 3/ data that are representative of agricultural areas and have been collected under accepted quality-assurance programs be used in future kriging efforts.

  1. Cancer Related-Knowledge - Small Area Estimates

    Cancer.gov

    These model-based estimates are produced using statistical models that combine data from the Health Information National Trends Survey, and auxiliary variables obtained from relevant sources and borrow strength from other areas with similar characteristics.

  2. Estimation Of Cultivated Area In Small Plot Agriculture In Africa For Food Security Purposes

    NASA Astrophysics Data System (ADS)

    Holecz, Francesco; Collivignarelli, Francesco; Barbieri, Massimo

    2013-12-01

    Cultivated area in small plot agriculture in Africa is estimated using a synergetic approach based on multi-sensor, multi-temporal Synthetic Aperture Radar (SAR) data. The method - which is based on the utilization of ALOS PALSAR-1, Cosmo-SkyMed, ENVISAT ASAR data involving different processing techniques - consists in the generation of three independent and complementary products, which in turn they are fused, enabling the generation of the cultivated area. Each intermediate product has a clear meaning within agriculture and food security: i) the potential crop extent prior to the crop season; ii) the potential area at start of the crop season; iii) the crop growth extent during the rainfed crop season. The proposed methodology has been implemented and demonstrated in Malawi. The obtained results show an overall accuracy exceeding 90%.

  3. Estimating crop biophysical properties from remote sensing data by inverting linked radiative transfer and ecophysiological models

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remote sensing technology can rapidly provide spatial information on crop growth status, which ideally could be used to invert radiative transfer models or ecophysiological models for estimating a variety of crop biophysical properties. However, the outcome of the model inversion procedure will be ...

  4. Airborne and ground-based remote sensing for the estimation of evapotranspiration and yield of bean, potato, and sugar beet crops

    NASA Astrophysics Data System (ADS)

    Jayanthi, Harikishan

    The focus of this research was two-fold: (1) extend the reflectance-based crop coefficient approach to non-grain (potato and sugar beet), and vegetable crops (bean), and (2) develop vegetation index (VI)-yield statistical models for potato and sugar beet crops using high-resolution aerial multispectral imagery. Extensive crop biophysical sampling (leaf area index and aboveground dry biomass sampling) and canopy reflectance measurements formed the backbone of developing of canopy reflectance-based crop coefficients for bean, potato, and sugar beet crops in this study. Reflectance-based crop coefficient equations were developed for the study crops cultivated in Kimberly, Idaho, and subsequently used in water availability simulations in the plant root zone during 1998 and 1999 seasons. The simulated soil water profiles were compared with independent measurements of actual soil water profiles in the crop root zone in selected fields. It is concluded that the canopy reflectance-based crop coefficient technique can be successfully extended to non-grain crops as well. While the traditional basal crop coefficients generally expect uniform growth in a region the reflectance-based crop coefficients represent the actual crop growth pattern (in less than ideal water availability conditions) in individual fields. Literature on crop canopy interactions with sunlight states that there is a definite correspondence between leaf area index progression in the season and the final yield. In case of crops like potato and sugar beet, the yield is influenced not only on how early and how quickly the crop establishes its canopy but also on how long the plant stands on the ground in a healthy state. The integrated area under the crop growth curve has shown excellent correlations with hand-dug samples of potato and sugar beet crops in this research. Soil adjusted vegetation index-yield models were developed, and validated using multispectral aerial imagery. Estimated yield images were

  5. Automatic corn-soybean classification using Landsat MSS data. I - Near-harvest crop proportion estimation. II - Early season crop proportion estimation

    NASA Technical Reports Server (NTRS)

    Badhwar, G. D.

    1984-01-01

    The techniques used initially for the identification of cultivated crops from Landsat imagery depended greatly on the iterpretation of film products by a human analyst. This approach was not very effective and objective. Since 1978, new methods for crop identification are being developed. Badhwar et al. (1982) showed that multitemporal-multispectral data could be reduced to a simple feature space of alpha and beta and that these features would separate corn and soybean very well. However, there are disadvantages related to the use of alpha and beta parameters. The present investigation is concerned with a suitable method for extracting the required features. Attention is given to a profile model for crop discrimination, corn-soybean separation using profile parameters, and an automatic labeling (target recognition) method. The developed technique is extended to obtain a procedure which makes it possible to estimate the crop proportion of corn and soybean from Landsat data early in the growing season.

  6. Airborne spectral radiometry for crop health and yield estimation

    NASA Astrophysics Data System (ADS)

    O'Mongain, Eon; Green, S. E.; Walsh, James E.; Burke, J.

    1995-01-01

    Spectral reflectance measurements have been made over sugar beet crops from a helicopter during 1991, 1992, and 1993 using a portable multichannel spectrometer system. In 1994 the studies were extended to demonstrate the potential for the measurement of stress in other crops. The observations are made from an altitude of about 150 m over the spectral range 420 nm to 810 nm, with a bandwidth of 5 nm. Downwelling solar irradiance and upwelling reflected irradiance are monitored by the multichannel spectrometer simultaneously. Both the absolute values of the reflectance at each wavelength and the variance of these reflectance values across each plot are shown to be related to the state of the crop. Concurrent agricultural ground truth consisting of fresh leaf weight and dry matter accumulation, is used in defining the crop yield models. The study aims to determine the appropriate radiometrically derived parameters which could be used as alternative model inputs. Although significant spectral differences exist and can be extracted by conventional band ratio or singular value decomposition techniques, the variance in the samples of ground truth data constrain the ability to define meaningful radiometric parameters. Improved experimental procedures are proposed.

  7. Estimating Crop Residue Distribution Using Airborne and Satellite Remote Sensing

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop residue management and reduced tillage are commonly accepted best management practices that improve soil quality through the sequestration of soil organic carbon. A major goal of this study was to evaluate remote sensing data for rapid quantification of conservation tillage at the field and wa...

  8. Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

    PubMed

    Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

    2015-06-01

    The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively.

  9. Paddy crop yield estimation in Kashmir Himalayan rice bowl using remote sensing and simulation model.

    PubMed

    Muslim, Mohammad; Romshoo, Shakil Ahmad; Rather, A Q

    2015-06-01

    The Kashmir Himalayan region of India is expected to be highly prone to the change in agricultural land use because of its geo-ecological fragility, strategic location vis-à-vis the Himalayan landscape, its trans-boundary river basins, and inherent socio-economic instabilities. Food security and sustainability of the region are thus greatly challenged by these impacts. The effect of future climate change, increased competition for land and water, labor from non-agricultural sectors, and increasing population adds to this complex problem. In current study, paddy rice yield at regional level was estimated using GIS-based environment policy integrated climate (GEPIC) model. The general approach of current study involved combining regional level crop database, regional soil data base, farm management data, and climatic data outputs with GEPIC model. The simulated yield showed that estimated production to be 4305.55 kg/ha (43.05 q h(-1)). The crop varieties like Jhelum, K-39, Chenab, China 1039, China-1007, and Shalimar rice-1 grown in plains recorded average yield of 4783.3 kg/ha (47.83 q ha(-1)). Meanwhile, high altitude areas with varieties like Kohsaar, K-78 (Barkat), and K-332 recorded yield of 4102.2 kg/ha (41.02 q ha(-1)). The observed and simulated yield showed a good match with R (2) = 0.95, RMSE = 132.24 kg/ha, respectively. PMID:25937498

  10. Methodology for estimating crop loss from acidic deposition

    SciTech Connect

    Irving, P.M.

    1982-01-01

    Crop losses affect the production, availability and cost of food, and therefore have important economic, social, and political implications especially during this period of rapid world population growth. The fact that air-borne pollutants affect vegetative growth has been known for more than a century. Recently, the acidic deposition phenomenon has gained increasing attention, especially when implicated as a factor potentially responsible for crop yield losses. Experimental approaches utilized in traditional pollution effects research include: field surveys, sensitivity classification, dose-response studies, and regional-impact evaluation. Acid rain is a unique pollutant having special problems associated with researching its effects. For example, the description of dose for this pollutant should include rain chemistry (not just pH), rainfall rate, duration of event, total deposition, droplet size, etc. These parameters must also be considered when simulating rain in controlled studies. Due to the potential for interactions with biotic and abiotic entities, factorial research designs and multivariate analyses may be necessary for investigations of acid-rain impacts on crops. Results from well-planned mechanistic studies and dose-response experiments may be used to predict effects (both positive and negative), assess economic impacts, and establish tolerance thresholds for this form of pollution.

  11. Estimation of net greenhouse gas balance using crop- and soil-based approaches: two case studies.

    PubMed

    Huang, Jianxiong; Chen, Yuanquan; Sui, Peng; Gao, Wansheng

    2013-07-01

    The net greenhouse gas balance (NGHGB), estimated by combining direct and indirect greenhouse gas (GHG) emissions, can reveal whether an agricultural system is a sink or source of GHGs. Currently, two types of methods, referred to here as crop-based and soil-based approaches, are widely used to estimate the NGHGB of agricultural systems on annual and seasonal crop timescales. However, the two approaches may produce contradictory results, and few studies have tested which approach is more reliable. In this study, we examined the two approaches using experimental data from an intercropping trial with straw removal and a tillage trial with straw return. The results of the two approaches provided different views of the two trials. In the intercropping trial, NGHGB estimated by the crop-based approach indicated that monocultured maize (M) was a source of GHGs (-1315 kg CO₂(-eq)ha(-1)), whereas maize-soybean intercropping (MS) was a sink (107 kg CO₂(-eq)ha(-1)). When estimated by the soil-based approach, both cropping systems were sources (-3410 for M and -2638 kg CO₂(-eq)ha(-1) for MS). In the tillage trial, mouldboard ploughing (MP) and rotary tillage (RT) mitigated GHG emissions by 22,451 and 21,500 kg CO₂(-eq)ha(-1), respectively, as estimated by the crop-based approach. However, by the soil-based approach, both tillage methods were sources of GHGs: -3533 for MP and -2241 kg CO₂(-eq)ha(-1) for RT. The crop-based approach calculates a GHG sink on the basis of the returned crop biomass (and other organic matter input) and estimates considerably more GHG mitigation potential than that calculated from the variations in soil organic carbon storage by the soil-based approach. These results indicate that the crop-based approach estimates higher GHG mitigation benefits compared to the soil-based approach and may overestimate the potential of GHG mitigation in agricultural systems.

  12. Area Estimation for Winter Wheat over the North China Plain Using a Sub-Pixel Classification Approach

    NASA Astrophysics Data System (ADS)

    van Hoolst, Roel; Dong, Qinghan; Eerens, Herman; Bydekrke, Lieven; Kerdiles, Herve

    2013-01-01

    This study examined the potential of sub-pixel classification for regional crop area estimation. The approach uses a neural network, trained on a high resolution crop map, to estimate sub-pixel crop area fractions using time series of S10 NDVI-composites of the 1 km resolution sensor SPOT-VEGETATION. The classification of the high resolution imagery such as LANDSAT TM was used to train the network. The application of such a trained network on an extended spatial area and temporal period has been studied, focusing especially on planting area of winter wheat on the North China Plain for the period 2005-2009.

  13. Estimating crop net primary production using inventory data and MODIS-derived parameters

    SciTech Connect

    Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; Izaurralde, Roberto C.

    2013-06-03

    National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale and over national and continental extents. Existing satellite-based NPP products tend to underestimate NPP on croplands. A new Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP. The method is documented here and evaluated for corn and soybean crops in Iowa and Illinois in years 2006 and 2007. The method includes a crop-specific enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), shortwave radiation data estimated using Mountain Climate Simulator (MTCLIM) algorithm and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that correspond to the Cropland Data Layer (CDL) land cover product. The modeling framework represented well the gradient of NPP across Iowa and Illinois, and also well represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 980 g C m-2 yr-1 and 420 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Estimated gross primary productivity (GPP) derived from AgI-LUE were in close agreement with eddy flux tower estimates. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

  14. Estimated Impacts of Emissions Reductions on Wheat and Maize Crops

    NASA Astrophysics Data System (ADS)

    Tebaldi, C.; Lobell, D. B.

    2015-12-01

    An ability to quantify the impacts associated with different emissions scenarios acrossa broad range of economic and environmental outcomes would be helpful for guidingpolicy on energy and greenhouse gas emissions. One outcome of particular interest,especially for food insecure populations, are effects on agricultural productivity. Inthis study we use empirical models of the relation between climate and CO2concentration on the one hand, and changes in crop yields on the other, tocharacterize the differential impacts on the future productivity of two major crops oftwo level of forcings: those associated with RCP4.5 and those associated withRCP8.5. This study is part of a larger project on the Benefits of ReducingAnthropogenic Climate changE (BRACE). We consider differential effects on maize andwheat yields at the global scale from expected changes in mean temperature andprecipitation under the two scenarios. We also characterize differential levels ofexposure to damaging heat extremes. Several time horizons are considered,characterizing expected impacts over the short, middle and long terms over the 21stcentury.

  15. Modeling of groundwater draft based on satellite-derived crop acreage estimation over an arid region of northwest India

    NASA Astrophysics Data System (ADS)

    Bhadra, Bidyut Kumar; Kumar, Sanjay; Paliwal, Rakesh; Jeyaseelan, A. T.

    2016-06-01

    Over-exploitation of groundwater for agricultural crops puts stress on the sustainability of natural resources in the arid region of Rajasthan state, India. Hydrogeological study of groundwater levels of the study area during the pre-monsoon (May to June), post-monsoon (October to November) and post-irrigation (February to March) seasons of 2004-2005 to 2011-2012 shows a steady decline of groundwater levels at the rate of 1.28-1.68 m/year, mainly due to excessive groundwater draft for irrigation. Due to the low density of the groundwater observation-well network in the study area, assessment of groundwater draft, and thus groundwater resource management, becomes a difficult task. To overcome the situation, a linear groundwater draft model (LGDM) has been developed based on the empirical relationship between satellite-derived crop acreage and the observed groundwater draft for the year 2003-2004. The model has been validated for a decade, during three year-long intervals (2005-2006, 2008-2009 and 2011-2012) using groundwater draft, estimated through a discharge factor method. Further, the estimated draft was validated through observed pumping data from random sampled villages (2011-2012). The results suggest that the developed LGDM model provides a good alternative to the estimation of groundwater draft based on satellite-based crop area in the absence of groundwater observation wells in arid regions of northwest India.

  16. Estimating Biophysical Crop Properties by a Machine Learning Model Inversion using Hyperspectral Imagery of Different Resolution

    NASA Astrophysics Data System (ADS)

    Preidl, S.; Doktor, D.

    2013-12-01

    This study investigates how image resolution and phenology affects the quality of biophysical variable estimation of different crop types. Hence, several hyperspectral at-sensor radiance images (400-2500 nm) of 1, 2 and 3 meter resolution were acquired by an AISA dual airborne system to estimate leaf chlorophyll content and leaf area index (LAI) of different crop types. The study area describes a climatic gradient that ranges from the Magdeburg Börde (130 meter a.s.l.) to the northeast of the Harz Mountain (450 meter a.s.l.), Germany. The 35 kilometer long flight strip is recorded on the same day at all three resolutions. Ground measurements were conducted simultaneously to the flight campaigns on selected crop fields. The SLC model was coupled with the atmospheric model MODTRAN4 to build up a look-up table (LUT) of simulated at-sensor radiances. To support a fast and more accurate inversion process, LUT-spectra were selected for model inversion which location in the PCA space (spanned by the first three principal components) is similar to the one of the measured spectra. A support vector regression (SVR) was trained on the reduced LUT to perform a pixel-based inversion of the hyperspectral images, subsequently. A multi-parameter sensitivity analysis was recently developed to define the most influential parameters for a reasonable model setup in the first place. This completes the development of an automated inversion process chain to estimate leaf and canopy biophysical properties. To achieve reasonable inversion results each pixel should be radiatively independent from its surrounding pixels. Image texture is used to calculate the second-order statistical variance between pixel pairs quantifying spatial heterogeneity throughout the spectral domain. The texture measurement can be employed as an uncertainty assessment of the biophysical variable estimation map. Results show that vegetated areas within the field are representing spectrally homogeneous systems. In

  17. Role of fish distribution on estimates of standing crop in a cooling reservoir

    USGS Publications Warehouse

    Barwick, D. Hugh

    1984-01-01

    Estimates of fish standing crop from coves in Keowee Reservoir, South Carolina, were obtained in May and August for 3 consecutive years. Estimates were significantly higher in May than in August for most of the major species of fish collected, suggesting that considerable numbers of fish had migrated from the coves by August. This change in fish distribution may have resulted from the operation of a 2,580-megawatt nuclear power plant which altered reservoir stratification. Because fish distribution is sensitive to conditions of reservoir stratification, and because power plants often alter reservoir stratification, annual cove sampling in August may not be sufficient to produce comparable estimates of fish standing crop on which to assess the impact of power plant operations on fish populations. Comparable estimates of fish standing crop can probably be obtained from cooling reservoirs by collecting annual samples at similar water temperatures and concentrations of dissolved oxygen.

  18. Establishing a method for estimating crop water requirements using the SEBAL method in Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, G.; Toulios, L.; Hadjimitsis, D.; Kountios, G.

    2014-08-01

    Water allocation to crops has always been of great importance in agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). The methodology set in this paper refers to COST action ES1106 (Agri-Wat) for determining crop water requirements as part of the water footprint and virtual water-trade.

  19. Remote sensing-based estimates of annual and seasonal emissions from crop residue burning in the contiguous United States.

    PubMed

    McCarty, Jessica L

    2011-01-01

    Crop residue burning is an extensive agricultural practice in the contiguous United States (CONUS). This analysis presents the results of a remote sensing-based study of crop residue burning emissions in the CONUS for the time period 2003-2007 for the atmospheric species of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), nitrogen dioxide (NO2, sulfur dioxide (SO2), PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter), and PM10 (PM < or = 10 microm in aerodynamic diameter). Cropland burned area and associated crop types were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) products. Emission factors, fuel load, and combustion completeness estimates were derived from the scientific literature, governmental reports, and expert knowledge. Emissions were calculated using the bottom-up approach in which emissions are the product of burned area, fuel load, and combustion completeness for each specific crop type. On average, annual crop residue burning in the CONUS emitted 6.1 Tg of CO2, 8.9 Gg of CH4, 232.4 Gg of CO, 10.6 Gg of NO2, 4.4 Gg of SO2, 20.9 Gg of PM2.5, and 28.5 Gg of PM10. These emissions remained fairly consistent, with an average interannual variability of crop residue burning emissions of +/- 10%. The states with the highest emissions were Arkansas, California, Florida, Idaho, Texas, and Washington. Most emissions were clustered in the southeastern United States, the Great Plains, and the Pacific Northwest. Air quality and carbon emissions were concentrated in the spring, summer, and fall, with an exception because of winter harvesting of sugarcane in Florida, Louisiana, and Texas. Sugarcane, wheat, and rice residues accounted for approximately 70% of all crop residue burning and associated emissions. Estimates of CO and CH4 from agricultural waste burning by the U.S. Environmental Protection Agency were 73 and 78% higher than the CO and CH4 emission estimates from this analysis, respectively. This analysis

  20. An Integrated Lysimeter and Satellite Imagery Approach for Estimating Crop Evapotranspiration

    NASA Astrophysics Data System (ADS)

    Goorahoo, D.; Cassel-Sharma, F.; Johnson, L.; Melton, F. S.

    2014-12-01

    Accurate estimation of crop water requirement (CWR) is essential for the implementation efficient irrigation schedules in an effort to optimize water use efficiency. This is particularly important in the central San Joaquin Valley (SJV), California, USA, where severe droughts have accentuated the need to conserve water and improve on-farm water management. In the current study, we adopt an integrated approach for estimation of crop evapotranspiration (ETc) involving the use of weighing lysimeters and satellite imagery. In the first phase of the study with the crop lysimeter, conducted on a clay loam soil with processing tomatoes grown under sub-surface drip irrigation, observations of crop ground cover were conducted weekly and evapotranspiration (ET) data were collected daily to derive relationships between crop coefficients and fractional cover. Data collected during the first year of the study, indicted that the crop coefficients (Kc) obtained at peak season were relatively higher than those generally reported for tomatoes commonly grown in the central SJV. Overall, there was a good correlation between fractional cover and crop coefficients (r2 = 0.91), with the average peak ET and Kc values ranging from 6 to 7 mm per day and from 0.8 to 0.9, respectively. Data obtained from satellite imagery, representing relatively larger spatial measurements than the lysimeters, are being compared with the surface observations from the lysimeters and will also be discussed in our presentation.

  1. Crop Evapotranspiration in San Joaquin Valley by Landsat Reflectance-based and Energy-balance Estimation Methods

    NASA Astrophysics Data System (ADS)

    Johnson, L.

    2011-12-01

    Evapotranspiration (ET) estimates are needed to support agricultural and natural resource management. Satellite based measurements offer the potential to efficiently monitor ET over large areas. In this study, two analysis methods were applied to Landsat-5 Thematic Mapper imagery to estimate crop evapotranspiration (ETc) in California's San Joaquin Valley. The Landsat L1T images (path 42, row 35) were collected monthly during the main growing season (Apr-Nov) in 2009. In the first method, the images were transformed to surface reflectance, and subsequently to NDVI. The NDVI was used to estimate mean fractional cover of several major crop types including almond, orange, grape, cotton, corn, alfalfa, and tomato across a total of 115 fields. Prior relationships developed by weighing lysimeter were used to convert fractional cover to a crop coefficient expressing ETc relative to grass reference evapotranspiration (ETo). Measurements of ETo by the California Irrigation Management Information System (CIMIS) were then used to calculate ETc on each overpass date. These reflectance-based estimates were compared with values retrieved by the Surface Energy Balance Algorithm for Land (SEBAL). SEBAL combined spectral radiances in Landsat optical and thermal bands with CIMIS meteorological data to derive ET as a surface energy budget residual by applying radiative, aerodynamic and energy balance physics in 25 computational steps. Reasonably strong agreement resulted, with mean absolute error (MAE) between the two approaches <1 mm/d, and coefficients of determination ranging from 0.78-0.90, for most of the crop types examined. Stronger agreement was found for fields deemed by SEBAL to contain unstressed crop (observed ET at-or-near potential) during satellite overpass, with MAE reductions averaging about 30 percent and coefficients of determination largely of range 0.90-0.94.

  2. Remote Estimation of Gross Primary Production in Crops at Field and Regional Levels

    NASA Astrophysics Data System (ADS)

    Gitelson, A. A.; Vina, A.; Verma, S. B.; Rundquist, D. C.

    2007-12-01

    Accurate estimation of spatially distributed CO2 fluxes is of great importance for regional and global studies of carbon balance. We have found that in irrigated and rainfed crops (maize and soybean), GPP is closely related to total crop chlorophyll content. The finding allowed development of a new technique for remote estimation of crop chlorophyll specifically for assessing gross primary production. The technique is based on reflectance in two spectral channels: the near-infrared and either the green or the red-edge. The technique provided accurate estimations of daily GPP in both crops. Validation using independent datasets for irrigated and rainfed maize and soybean documented the robustness of the technique. We report also about applying the developed technique for GPP retrieval from data acquired by both an airborne imaging spectrometer (AISA-Eagle) and Landsat ETM+. The Chlorophyll Index, retrieved from Landsat ETM+ data, was found to be an accurate surrogate measure for daily crop GPP with a root mean square error of GPP prediction of less than 1.58 g C m-2d-1 in a GPP range of 1.88 g C m-2d-1 to 23.1 g C m-2d-1. These results suggest new possibilities for analyzing the spatio-temporal variation of the GPP of crops using not only the extensive archive of Landsat Thematic Mapper imagery acquired since the early 1980s but also the 500-m/pixel data currently being acquired by MODIS.

  3. Projecting crop yield in northern high latitude area.

    PubMed

    Matsumura, Kanichiro

    2014-01-01

    validation periods is used. To show the reproducing projection between observed and calculated values, the root mean squared error for skill score (RMSE SS) with the persistence model serving as the reference model is used. The persistence model is used as a benchmark. The results show that SADs near USA border show better RMSE SS values and mode 3's time coefficients can be a useful predictor especially for inland province such as Manitoba. Among 27 Canadian Prairie's SADs with perfect yield data, 67% of Alberta's SADs, 86% of Manitoba's SADs, and 77% of Saskatchewan's SADs can get positive skill scores. In each SAD, future yield projection is calculated applying predictors in 2013 for the obtained eight sets of models and eight sets of forecasted values in 2013 are averaged and a near future projection result is obtained. Series of outputs including calculated forecasted yield value in each SAD is provided by smart phone application. A system for providing climatic condition for a point with a permission of Climatic Research Unit - University of East Anglia and for obtaining patent is proposed. There are several patented systems similar to the system proposed in this paper. However, these patents are different in essence. The system proposed in this paper consists of two parts. First part is to estimate equations using time series data. The second part is to acquire and apply latest climatic conditions for obtained equations and calculate future projection. If the procedure is refined and devices are originally developed, series of idea can be patented. For future work, crop index, Hokkaido is also introduced. PMID:25733071

  4. Remote estimation of gross primary production in crops: Problems and solutions

    NASA Astrophysics Data System (ADS)

    Gitelson, A. A.

    2006-05-01

    Accurate estimation of spatially distributed chlorophyll content (Chl) in crops is of great importance for regional and global studies of carbon balance and responses to fertilizer (e.g., nitrogen) application. A recently developed conceptual a three-band reflectance model was applied for remotely estimating Chl in maize and soybean crops. We tuned the spectral regions to be included in the model, according to the optical characteristics of the crops studied, and showed that the developed technique allowed accurate estimation of total Chl in both crops, explaining more than 92% of Chl variation. We have found that in irrigated and rainfed maize and soybean mid-day GPP is closely related to total crop chlorophyll content. Thus, we found way to accurately estimate mid-day GPP in both crops under rainfed and irrigated conditions with root mean square error of GPP estimation of less than 0.3 mg CO2/m2s in maize (GPP ranged from 0 to 3.1 mg CO2/m2s) and less than 0.2 mg CO2/m2s in soybean (GPP ranged from 0 to 1.8 mg CO2/m2s). Validation using an independent dataset for irrigated and rainfed maize showed robustness of the technique; RMSE of GPP prediction was less than 0.27 mg CO2/m2s. This new technique shows great potential for remotely tracking the GPP and physiological status of crops, with contrasting canopy architectures, and their responses to environmental changes.

  5. Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The scale mismatch between remotely sensed observations and crop growth models simulated state variables decreases the reliability of crop yield estimates. To overcome this problem, we used a two-step data assimilation phases: first we generated a complete leaf area index (LAI) time series by combin...

  6. Irrigated rice area estimation using remote sensing techniques: Project's proposal and preliminary results. [Rio Grande do Sul, Brazil

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Deassuncao, G. V.; Moreira, M. A.; Novaes, R. A.

    1984-01-01

    The development of a methodology for annual estimates of irrigated rice crop in the State of Rio Grande do Sul, Brazil, using remote sensing techniques is proposed. The project involves interpretation, digital analysis, and sampling techniques of LANDSAT imagery. Results are discussed from a preliminary phase for identifying and evaluating irrigated rice crop areas in four counties of the State, for the crop year 1982/1983. This first phase involved just visual interpretation techniques of MSS/LANDSAT images.

  7. Reconstructing rice phenology curves with frequency-based analysis and multi-temporal NDVI in double-cropping area in Jiangsu, China

    NASA Astrophysics Data System (ADS)

    Wang, Hongshuo; Lin, Hui; Munroe, Darla K.; Zhang, Xiaodong; Liu, Pengfei

    2016-06-01

    Crop phenology retrieval in the double-cropping area of China is of great significance in crop yield estimation and water management under the influences of global change. In this study, rice phenology in Jiangsu Province, China was extracted from multi-temporal MODIS NDVI using frequency-based analysis. Pure MODIS pixels of rice were selected with the help of TM images. Discrete Fourier Transformation (DFT), Discrete Wavelet Transformation (DWT), and Empirical Mode Decomposition (EMD) were performed to decompose time series into components of different frequencies. Rice phenology in the double-cropping area is mainly located on the last 2 IMFs of EMD and the first 2‒3 frequencies of DFT and DWT. Compared with DFT and DWT, EMD is limited to fewer frequencies. Multi-temporal MODIS NDVI data combined with frequency-based analysis can retrieve rice phenology dates with on average 79% valid estimates. The sorting result for effective estimations from different methods is DWT (85%)>EMD (80%)>DFT (74%). Planting date (88%) is easier to estimate than harvesting date (70%). Rice planting date is easily affected by the former cropping mode within the same year in a double-cropping region. This study sheds light on understanding crop phenology dynamics in the frequency domain of multi-temporal MODIS data.

  8. [Quantification of crop residue burned areas based on burning indices using Landsat 8 image].

    PubMed

    Ma, Jian-hang; Song, Kai-shar; Wen, Zhi-dan; Shao, Tian-tian; Li, Bo-nan; Qi, Cai

    2015-11-01

    Crop residue burning leads to atmospheric pollution and is an enormous waste of crop residue resource. Crop residue burning can be monitored timely in large regions as the fire points can be recognized through remotely sensed image via thermal infrared bands. However, the area, the detailed distribution pattern and especially the severity of the burning areas cannot be derived only by the thermal remote sensing approach. The burning index, which was calculated with two or more spectral bands at where the burned and unburned areas have distinct spectral characteristics, is widely used in the forest fire investigation. However its potential application for crop residue burning evaluation has not been explored. With two Landsat 8 images that cover a part of the Songnen Plain, three burning indices, i.e., the normalized burned ratio (NBR), the normalized burned ratio incorporating the thermal band (NBRT), and the burned area index (BAI), were used to classify the crop residue burned and unburned areas. The overall classification accuracies were 91.9%, 92.3%, and 87.8%, respectively. The correlation analysis between the indices and the crop residue coverage indicated that the NBR and NBRT were positively correlated with the crop residue coverage (R2 = 0.73 and 0.64, respectively) with linear regression models, while the BAI was exponentially correlated with the crop residue coverage (R2 = 0.68). The results indicated that the use of burning indices in crop residue burning monitoring could quantify crop residue burning severity and provide valuable data for evaluating atmospheric pollution.

  9. [Quantification of crop residue burned areas based on burning indices using Landsat 8 image].

    PubMed

    Ma, Jian-hang; Song, Kai-shar; Wen, Zhi-dan; Shao, Tian-tian; Li, Bo-nan; Qi, Cai

    2015-11-01

    Crop residue burning leads to atmospheric pollution and is an enormous waste of crop residue resource. Crop residue burning can be monitored timely in large regions as the fire points can be recognized through remotely sensed image via thermal infrared bands. However, the area, the detailed distribution pattern and especially the severity of the burning areas cannot be derived only by the thermal remote sensing approach. The burning index, which was calculated with two or more spectral bands at where the burned and unburned areas have distinct spectral characteristics, is widely used in the forest fire investigation. However its potential application for crop residue burning evaluation has not been explored. With two Landsat 8 images that cover a part of the Songnen Plain, three burning indices, i.e., the normalized burned ratio (NBR), the normalized burned ratio incorporating the thermal band (NBRT), and the burned area index (BAI), were used to classify the crop residue burned and unburned areas. The overall classification accuracies were 91.9%, 92.3%, and 87.8%, respectively. The correlation analysis between the indices and the crop residue coverage indicated that the NBR and NBRT were positively correlated with the crop residue coverage (R2 = 0.73 and 0.64, respectively) with linear regression models, while the BAI was exponentially correlated with the crop residue coverage (R2 = 0.68). The results indicated that the use of burning indices in crop residue burning monitoring could quantify crop residue burning severity and provide valuable data for evaluating atmospheric pollution. PMID:26915202

  10. Stratum variance estimation for sample allocation in crop surveys. [Great Plains Corridor

    NASA Technical Reports Server (NTRS)

    Perry, C. R., Jr.; Chhikara, R. S. (Principal Investigator)

    1980-01-01

    The problem of determining stratum variances needed in achieving an optimum sample allocation for crop surveys by remote sensing is investigated by considering an approach based on the concept of stratum variance as a function of the sampling unit size. A methodology using the existing and easily available information of historical crop statistics is developed for obtaining initial estimates of tratum variances. The procedure is applied to estimate stratum variances for wheat in the U.S. Great Plains and is evaluated based on the numerical results thus obtained. It is shown that the proposed technique is viable and performs satisfactorily, with the use of a conservative value for the field size and the crop statistics from the small political subdivision level, when the estimated stratum variances were compared to those obtained using the LANDSAT data.

  11. A root zone modelling approach to estimating groundwater recharge from irrigated areas

    NASA Astrophysics Data System (ADS)

    Jiménez-Martínez, J.; Skaggs, T. H.; van Genuchten, M. Th.; Candela, L.

    2009-03-01

    SummaryIn irrigated semi-arid and arid regions, accurate knowledge of groundwater recharge is important for the sustainable management of scarce water resources. The Campo de Cartagena area of southeast Spain is a semi-arid region where irrigation return flow accounts for a substantial portion of recharge. In this study we estimated irrigation return flow using a root zone modelling approach in which irrigation, evapotranspiration, and soil moisture dynamics for specific crops and irrigation regimes were simulated with the HYDRUS-1D software package. The model was calibrated using field data collected in an experimental plot. Good agreement was achieved between the HYDRUS-1D simulations and field measurements made under melon and lettuce crops. The simulations indicated that water use by the crops was below potential levels despite regular irrigation. The fraction of applied water (irrigation plus precipitation) going to recharge ranged from 22% for a summer melon crop to 68% for a fall lettuce crop. In total, we estimate that irrigation of annual fruits and vegetables produces 26 hm 3 y -1 of groundwater recharge to the top unconfined aquifer. This estimate does not include important irrigated perennial crops in the region, such as artichoke and citrus. Overall, the results suggest a greater amount of irrigation return flow in the Campo de Cartagena region than was previously estimated.

  12. Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products

    NASA Astrophysics Data System (ADS)

    Vintrou, Elodie; Desbrosse, Annie; Bégué, Agnès; Traoré, Sibiry; Baron, Christian; Lo Seen, Danny

    2012-02-01

    In Africa, food security early warning systems use satellite-derived data concerning crop conditions and agricultural production. Such systems can be improved if they are provided with a more reliable estimation of the cultivated area at national scale. This paper evaluates the potential of using time series from the MODerate resolution Imaging Spectroradiometer MOD13Q1 (16-day composite of normalized difference vegetation index at 250 m resolution) to extract cultivated areas in the fragmented rural landscapes of Mali. To this end, we first stratified Southern Mali into 13 rural landscapes based on the spatio-temporal variability of NDVI and textural indices, using an object-oriented classification scheme. The accuracy of the resulting map (MODIS crop) and how it compares with existing coarse-resolution global land products (GLC2000 Africa, GLOBCOVER, MODIS V05 and ECOCLIMAP-II), was then assessed against six crop/non-crop maps derived from SPOT 2.5 m resolution images used as references. For crop areal coverage, the MODIS crop cultivated map was successful in assessing the overall cultivated area at five out of the six validation sites (less than 6% of the absolute difference), while in terms of crop spatial distribution, the producer accuracy was between 33.1% and 80.8%. This accuracy was linearly correlated with the mean patch size index calculated on the SPOT crop maps ( r2 = 0.8). Using the Pareto boundary as an accuracy assessment method at the study sites, we showed that (i) 20-40% of the classification crop error was due to the spatial resolution of the MODIS sensor (250 m), and that (ii) compared to MODIS V05, which otherwise performed better than the other existing products, MODIS crop generally minimized omission-commission errors. A spatial validation of the different products was carried out using SPOT image classifications as reference. In the corresponding error matrices, the fraction of correctly classified pixels for our product was 70%, compared

  13. Estimating crop net primary production using national inventory data and MODIS-derived parameters

    NASA Astrophysics Data System (ADS)

    Bandaru, Varaprasad; West, Tristram O.; Ricciuto, Daniel M.; César Izaurralde, R.

    2013-06-01

    National estimates of spatially-resolved cropland net primary production (NPP) are needed for diagnostic and prognostic modeling of carbon sources, sinks, and net carbon flux between land and atmosphere. Cropland NPP estimates that correspond with existing cropland cover maps are needed to drive biogeochemical models at the local scale as well as national and continental scales. Existing satellite-based NPP products tend to underestimate NPP on croplands. An Agricultural Inventory-based Light Use Efficiency (AgI-LUE) framework was developed to estimate individual crop biophysical parameters for use in estimating crop-specific NPP over large multi-state regions. The method is documented here and evaluated for corn (Zea mays L.) and soybean (Glycine max L. Merr.) in Iowa and Illinois in 2006 and 2007. The method includes a crop-specific Enhanced Vegetation Index (EVI), shortwave radiation data estimated using the Mountain Climate Simulator (MTCLIM) algorithm, and crop-specific LUE per county. The combined aforementioned variables were used to generate spatially-resolved, crop-specific NPP that corresponds to the Cropland Data Layer (CDL) land cover product. Results from the modeling framework captured the spatial NPP gradient across croplands of Iowa and Illinois, and also represented the difference in NPP between years 2006 and 2007. Average corn and soybean NPP from AgI-LUE was 917 g C m-2 yr-1 and 409 g C m-2 yr-1, respectively. This was 2.4 and 1.1 times higher, respectively, for corn and soybean compared to the MOD17A3 NPP product. Site comparisons with flux tower data show AgI-LUE NPP in close agreement with tower-derived NPP, lower than inventory-based NPP, and higher than MOD17A3 NPP. The combination of new inputs and improved datasets enabled the development of spatially explicit and reliable NPP estimates for individual crops over large regional extents.

  14. 78 FR 38483 - Area Risk Protection Insurance Regulations and Area Risk Protection Insurance Crop Provisions

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-06-26

    .... See the Notice related to 7 CFR part 3015, subpart V, published at 48 FR 29115, June 24, 1983... the Federal Register at 76 FR 44200-44224. The public was afforded 60 days to submit comments after..., ARPI Corn Crop Insurance Provisions, ARPI Cotton Crop Insurance Provisions, ARPI Forage Crop...

  15. The auxiliary use of LANDSAT data in estimating crop acreages: Results of the 1975 Illinois crop-acreage experiment

    NASA Technical Reports Server (NTRS)

    Gleason, C. (Principal Investigator); Starbuck, R. R.; Sigman, R. S.; Hanuschak, G. A.; Craig, M. E.; Cook, P. W.; Allen, R. D.

    1977-01-01

    The author has identified the following significant results. It was found that classifier performance was influenced by a number of temporal, methodological, and geographical factors. Best results were obtained when corn was tasselled and near the dough stage of development. Dates earlier or later in the growing season produced poor results. Atmospheric effects on results cannot be independently measured or completely separated from the effects due to the maturity stage of the crops. Poor classifier performance was observed in areas where considerable spectral confusion was present.

  16. Comparison of Crop Evapotranspiration Estimates from Reference Evapotranspiration Equations and a Variational Data Assimilation Approach

    NASA Astrophysics Data System (ADS)

    Bateni, S. M.; Michalik, T.; Multsch, S.; Breuer, L.

    2015-12-01

    Crop evapotranspiration (ETc) is a key component of water resources management in irrigation of farmlands as it determines the crop water consumption. Numerous methods have been used to estimate ETc for scheduling irrigation and evaluating the soil water balance. However, there is a significant difference in ETc estimates from various models, which leads to a large uncertainty in the soil water balance, crop water consumption, and irrigation scheduling. In this study, several commonly-used ETc equations (Turc, Priestley-Taylor, Hargreaves-Samani, Penman-Monteith) are compared with the variational data assimilation approach (VDA) of Bateni et al. (2013). The ETc equations initially estimate the reference evapotranspiration (ETo), which is the evapotranspiration from a healthy and actively-transpiring grass field with ample water in the soil. Thereafter, ETc is calculated by multiplying ETo by the crop coefficient (Kc), which accounts for the crop type and soil water stress. To properly apply the Kc to non-standard conditions, a daily water balance estimation for the root zone is required, which is done by two soil water budget models (Cropwat, Hydrus-1D) that compute incoming and outgoing water flows in the soil profile. In contrast to these methods that estimate ETc in two steps, the VDA approach directly predicts ETc by assimilating sequences of land surface temperature into the heat diffusion equation and thus it is expected to provide more accurate ETc estimates. All approaches are applied over three cropland sites namely, Bondville, Fermi, and Mead in the summer of 2006 and 2007. These sites are part of the AmeriFlux network and provide a wide variety of hydrological conditions. The results show that the variational data assimilation approach performs better compared to other equations.

  17. A National Assessment of Promising Areas for Switchgrass, Hybrid Poplar, or Willow Energy Crop Production

    SciTech Connect

    Graham, R.L.; Walsh, M.E.

    1999-02-01

    The objective of this paper is to systematically assess the cropland acreage that could support energy crops and the expected farm gate and delivered prices of energy crops. The assessment is based on output from two modeling approaches: (1) the Oak Ridge County-Level Energy Crop (ORECCL) database (1996 version) and (2) the Oak Ridge Integrated Bioenergy Analysis System (ORIBAS). The former provides county-level estimates of suitable acres, yields, and farmgate prices of energy crops (switchgrass, hybrid poplar, willow) for all fifty states. The latter estimates delivered feedstock prices and quantities within a state at a fine resolution (1 km2) and considers the interplay between transportation costs, farmgate prices, cropland density, and facility demand. It can be used to look at any type of feedstock given the appropriate input parameters. For the purposes of this assessment, ORIBAS has been used to estimate farmgate and delivered switchgrass prices in 11 states (AL, FL, GA, IA, M N, MO, ND, NE, SC, SD, and TN). Because the potential for energy crop production can be considered from several perspectives, and is evolving as policies, economics and our basic understanding of energy crop yields and production costs change, this assessment should be viewed as a snapshot in time.

  18. An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans

    NASA Technical Reports Server (NTRS)

    Hixson, M. M.; Bauer, M. E.; Scholz, D. K.

    1980-01-01

    During the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate and timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans. Multitemporally registered Landsat MSS data from four acquisitions during the 1978 growing season were used in classification of eight sample segments in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on spectral differences in crops at certain growth stages.

  19. Estimating the Soil Thermal Conductivity in a Agricultural Crop Site in Southern Brazil

    NASA Astrophysics Data System (ADS)

    Zimmer, Tamíres; Roberti, Debora; Moreira, Virnei; Silveira, Marcos

    The thermal conductivity is higher when the heat storage is higher and the soil surface temperature is lower. The soil thermal conductivity is also dependant on the soil texture, porosity and moisture. Therefore, it varies from soil to soil and in the same soil, depending on its soil moisture. In the present work, it is shown soil thermal conductivity estimates in a agricultural crop located at the Cruz Alta city in southern Brazil. Also the dynamic of soil heat flux (G) is analyzed and the soil thermal conductivity (Ks) is estimated using experimental data form soil heat flux and soil temperature in a agricultural crop farm in a subtropical location in Southern Brazil. In this specific site, there is a crop rotation scheme along the year. The soil type is Rhodic Hapludox (FAO) or Typic Haplorthox (US Soil Taxonomy), characterized as a deep, clay soil. The experimental soil heat flux was compared with estimated soil heat flux by two forms: (1) using a known Ks from literature for this type of soil; (2) using Ks estimated using the inversion of the equation Qg=-ks* ((T2-T1)/ (Z2-Z1)), where T1 and T2 are the temperature in different layers above the soil and Z2-Z1 is the difference between the positions in temperature measurement. The general results agree with the literature for the specific agricultural crop for Ks values in the current study for the measurement period.

  20. Assimilation of active and passive microwave observations for improved estimates of soil moisture and crop growth

    Technology Transfer Automated Retrieval System (TEKTRAN)

    An Ensemble Kalman Filter-based data assimilation framework that links a crop growth model with active and passive (AP) microwave models was developed to improve estimates of soil moisture (SM) and vegetation biomass over a growing season of soybean. Complementarities in AP observations were incorpo...

  1. Productivity and carbon dioxide exchange of the leguminous crops: Estimates from flux tower measurements

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Net CO2 exchange data on legume crops at 17 flux tower sites in North America and 3 sites in Europe representing 29 site-years of measurements were partitioned into gross photosynthesis and ecosystem respiration using a light-response function method, resulting in new estimates of ecosystem-scale ec...

  2. Determination of the optimal level for combining area and yield estimates

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator); Hixson, M. M.; Jobusch, C. D.

    1981-01-01

    Several levels of obtaining both area and yield estimates of corn and soybeans in Iowa were considered: county, refined strata, refined/split strata, crop reporting district, and state. Using the CCEA model form and smoothed weather data, regression coefficients at each level were derived to compute yield and its variance. Variances were also computed with stratum level. The variance of the yield estimates was largest at the state and smallest at the county level for both crops. The refined strata had somewhat larger variances than those associated with the refined/split strata and CRD. For production estimates, the difference in standard deviations among levels was not large for corn, but for soybeans the standard deviation at the state level was more than 50% greater than for the other levels. The refined strata had the smallest standard deviations. The county level was not considered in evaluation of production estimates due to lack of county area variances.

  3. Irrigation Trials for ET Estimation and Water Management in California Specialty Crops

    NASA Astrophysics Data System (ADS)

    Johnson, L.; Cahn, M.; Martin, F.; Lund, C.; Melton, F. S.

    2012-12-01

    Accurate estimation of crop evapotranspiration (ETc) can support efficient irrigation water management, which in turn brings benefits including surface water conservation, mitigation of groundwater depletion/degradation, energy savings, and crop quality assurance. Past research in California has revealed strong relationships between canopy fractional cover (Fc) and ETc of certain specialty crops, while additional research has shown the potential of monitoring Fc by satellite remote sensing. California's Central Coast is the leading region of cool season vegetable production in the U.S. Monterey County alone produces more than 80,000 ha of lettuce and broccoli (about half of U.S. production), valued at $1.5 billion in 2009. Under this study, we are conducting ongoing irrigation trials on these crops at the USDA Agricultural Research Station (Salinas) to compare irrigation scheduling via plant-based ETc approaches, by way of Fc, with current industry standard-practice. The following two monitoring approaches are being evaluated - 1) a remote sensing model employed by NASA's prototype Satellite Irrigation Management System, and 2) an online irrigation scheduling tool, CropManage, recently developed by U.C. Cooperative Extension. Both approaches utilize daily grass-reference ETo data as provided by the California Irrigation Management Irrigation System (CIMIS). A sensor network is deployed to monitor applied irrigation, volumetric soil water content, soil water potential, deep drainage, and standard meteorologic variables in order to derive ETc by a water balance approach. Evaluations of crop yield and crop quality are performed by the research team and by commercial growers. Initial results to-date indicate that applied water reductions based on Fc measurements are possible with little-to-no impact on yield of crisphead lettuce (Lactuca sativa). Additional results for both lettuce and broccoli trials, conducted during summer-fall 2012, are presented with respect to

  4. Development of High Resolution Data for Irrigated Area and Cropping Patterns in India

    NASA Astrophysics Data System (ADS)

    K a, A.; Mishra, V.

    2015-12-01

    Information of crop phenology and its individual effect on irrigation is essential to improve the simulation of land surface states and fluxes. We use moderate resolution imaging spectroradiometer (MODIS) - Normalized difference vegetation index (NDVI) at 250 m resolution for monitoring temporal changes in irrigation and cropping patterns in India. We used the obtained dataset of cropping pattern for quantifying the effect of irrigation on land surface states and fluxes by using an uncoupled land surface model. The cropping patterns are derived by using the planting, heading, harvesting, and growing dates for each agro-ecological zone separately. Moreover, we developed a high resolution irrigated area maps for the period of 1999-2014 for India. The high resolution irrigated area was compared with relatively coarse resolution (~ 10km) irrigated area from the Food and Agricultural Organization. To identify the seasonal effects we analyzed the spatial and temporal change of irrigation and cropping pattern for different temporal seasons. The new irrigation area information along with cropping pattern was used to study the water budget in India using the Noah Land surface Model (Noah LSM) for the period of 1999-2014.

  5. How Universal Is the Relationship Between Remotely Sensed Vegetation Indices (VI) and Crop Leaf Area Index (LAI)?

    NASA Technical Reports Server (NTRS)

    Kang, Yanghui; Ozdogan, Mutlu; Zipper, Samuel C.; Roman, Miguel

    2016-01-01

    Global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. This research enables the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

  6. Thermography for estimating near-surface soil moisture under developing crop canopies

    NASA Technical Reports Server (NTRS)

    Heilman, J. L.; Moore, D. G.

    1980-01-01

    Previous investigations of thermal infrared techniques using remote sensors (thermography) for estimating soil water content have been limited primarily to bare soil. Ground-based and aircraft investigations were conducted to evaluate the potential for extending the thermography approach to developing crop canopies. A significant exponential relationship was found between the volumetric soil water content in the 0-4 cm soil layer and the diurnal difference between surface soil temperature measured at 0230 and 1330 LST (satellite overpass times of NASA's Heat Capacity Mapping Mission - HCMM). Surface soil temperatures were estimated using minimum air temperature, percent cover of the canopy and remote measurements of canopy temperature. Results of the investigation demonstrated that thermography can potentially be used to estimate soil temperature and soil moisture throughout a complete growing season for a number of different crops and soils.

  7. Taxonomic classification of world map units in crop producing areas of Argentina and Brazil with representative US soil series and major land resource areas in which they occur

    NASA Technical Reports Server (NTRS)

    Huckle, H. F. (Principal Investigator)

    1980-01-01

    The most probable current U.S. taxonomic classification of the soils estimated to dominate world soil map units (WSM)) in selected crop producing states of Argentina and Brazil are presented. Representative U.S. soil series the units are given. The map units occurring in each state are listed with areal extent and major U.S. land resource areas in which similar soils most probably occur. Soil series sampled in LARS Technical Report 111579 and major land resource areas in which they occur with corresponding similar WSM units at the taxonomic subgroup levels are given.

  8. Large Area Crop Inventory Experiment (LACIE). Development of procedure M for multicrop inventory, with tests of a spring-wheat configuration

    NASA Technical Reports Server (NTRS)

    Horvath, R. (Principal Investigator); Cicone, R.; Crist, E.; Kauth, R. J.; Lambeck, P.; Malila, W. A.; Richardson, W.

    1979-01-01

    The author has identified the following significant results. An outgrowth of research and development activities in support of LACIE was a multicrop area estimation procedure, Procedure M. This procedure was a flexible, modular system that could be operated within the LACIE framework. Its distinctive features were refined preprocessing (including spatially varying correction for atmospheric haze), definition of field like spatial features for labeling, spectral stratification, and unbiased selection of samples to label and crop area estimation without conventional maximum likelihood classification.

  9. Estimating water and nitrate leaching in tree crops using inverse modelled plant and soil hydraulic properties

    NASA Astrophysics Data System (ADS)

    Couvreur, Valentin; Kandelous, Maziar; Mairesse, Harmony; Baram, Shahar; Moradi, Ahmad; Pope, Katrin; Hopmans, Jan

    2015-04-01

    Groundwater quality is specifically vulnerable in irrigated agricultural lands in California and many other (semi-)arid regions of the world. The routine application of nitrogen fertilizers with irrigation water in California is likely responsible for the high nitrate concentrations in groundwater, underlying much of its main agricultural areas. To optimize irrigation/fertigation practices, it is essential that irrigation and fertilizers are applied at the optimal concentration, place, and time to ensure maximum root uptake and minimize leaching losses to the groundwater. The applied irrigation water and dissolved fertilizer, root nitrate and water uptake interact with soil and root properties in a complex manner that cannot easily be resolved. It is therefore that coupled experimental-modelling studies are required to allow for unravelling of the relevant complexities that result from typical variations of crop properties, soil texture and layering across farmer-managed fields. A combined field monitoring and modelling approach was developed to quantify from simple measurements the leaching of water and nitrate below the root zone. The monitored state variables are soil water content within the root zone, soil matric potential below the root zone, and nitrate concentration in the soil solution. Plant and soil properties of incremented complexity are optimized with the software HYDRUS in an inverse modelling scheme, which allows estimating leaching under constraint of hydraulic principles. Questions of optimal irrigation and fertilization timing can then be addressed using predictive results and global optimization algorithms.

  10. Estimations of ozone damage to selected crops grown in southern California

    SciTech Connect

    Leung, S.K.; Reed, W.; Geng, S.

    1982-02-01

    The information presented in this paper is concerned with the effects of ambient ozone on crop yield reduction and the resultant economic losses. Yield data for nine crops within the South Coast Air Basin (SCAB) of California were obtained for the 12-year period, 1964 through 1975. Ozone concentrations, temperature, precipitation, and relative humidity data were related to the yields by using regression models. Estimated yield reductions due to ozone for 1975, varied from zero to 57% depending on crop and location. Economic welfare losses calculated from the yield reductions were $57.3 and $45.7 million for producer's and consumer's surplus, respectively. The total loss from ozone to agriculture related economic sectors determined by input-output analysis was $276 million in the SCAB and $36.6 million in the remainder of the state.

  11. On Estimating Crop Coefficients and Decoupling Factors of Forest Ecosystems in East Asia

    NASA Astrophysics Data System (ADS)

    Kang, M.; Kim, J.; Kwon, H.; Hirano, T.; Saigusa, N.; Takagi, K.; Yu, G.

    2012-12-01

    For effective water management, the quantification of evapotranspiration (ET) is imperative. Considering the difficulty of measurement and adequate simulation of ET in large areas, the crop coefficients (Kc=ETc adj/ETo/Ks; where ETc adj is the adjusted evapotranspiration, ETo is the reference crop evapotranspiration estimated by the FAO56-PM method, and Ks is the water stress coefficient) and the decoupling factors (Ω=ETa/ETp; where ETa is the actual evapotranspiration, and ETp is the potential evapotranspiration estimated by the Penman-Monteith equation) are valuable information for the assessment of regional ET. In this study, we determined the Kc and Ω of seven forest ecosystems in East Asia (i.e., temperate and coniferous forests in Gwangneung, Korea, GDK and GCK, respectively; cool temperate forests in Changbaishan, China, CBS, in Takayama and Teshio, Japan, TKY and TSE, respectively; subtropical forest in Xishuangbanna, Southern China, BNS; tropical forest in Palangkaraya, Indonesia, PDF) using the multi-year observed ET by eddy covariance technique. Annual ETo ranged from 443 mm at the TKY site to 1368 mm at the PDF site. Annual ETp ranged from 835 mm at the TSE site to 2466 mm at the PDF site. The Kc and Ω for the (cool) temperate forests showed a clear seasonality with the minimum (~0.3 of Kc and ~0 of Ω) in winter and the maximum in summer or early autumn. The maxima of Kc were different among the sites and ranged from 0.6 at the TSE site to 1.2 at the BNS site. Unlike the maximum Kc, the maxima of Ω were similar among the temperate forests (0.4~0.5) and between the tropical forests (~0.6). Implications of the results are discussed in terms of usefulness and accuracy of using Kc and Ω. Acknowledgement - This study was supported by the Korea Meteorological Administration Research and Development Program under Grant CATER 2012-3030. The flux database was provided by CarboEastAsia - A3 Foresight Program and KoFlux.

  12. Estimating the Sensitivity of CLM-Crop to Plant Date and Growing Season Length

    NASA Astrophysics Data System (ADS)

    Drewniak, B. A.; Kotamarthi, V. R.

    2012-12-01

    The Community Land Model (CLM), the land component of the Community Earth System Model (CESM), is designed to estimate the land surface response to climate through simulated vegetation phenology and soil carbon and nitrogen dynamics. Since human influences play a significant role shaping the land surface, the vegetation has been expanded to include agriculture (CLM-Crop) for three crop types: corn, soybean, and spring wheat. CLM-Crop parameters, which define crop phenology, are optimized against AmeriFlux observations of gross primary productivity, net ecosystem exchange, and stored biomass and carbon, for two sites in the U.S. growing corn and soybean. However, there is uncertainty in the measurements and using a small subset of data to determine model parameters makes validation difficult. In order to account for the differences in plant behavior across climate zones, an input dataset is used to define the planting dates and the length of the growing season. In order to improve model performance, and to understand the impacts of uncertainty from the input data, we evaluate the sensitivity of crop productivity and production against planting date and the length of the growing season. First, CLM-Crop is modified to establish plant date based on temperature trends for the previous 10-day period, constrained against the range of observed planting dates. This new climate-based model is compared with the standard fixed plant dates to determine how sensitive the model is to when seeding occurs, and how comparable the climate calculated plant dates are to the fixed dates. Next, the length of the growing season will be revised to account for an alternative climate. Finally, both the climate-based planting and new growth season will be simulated together. Results of the different model runs will be compared to the standard model and to observations to determine the importance of planting date and growing season length on crop productivity and yield.

  13. Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

    PubMed

    Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

    2016-05-30

    Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data. PMID:27410085

  14. Effects of LiDAR point density, sampling size and height threshold on estimation accuracy of crop biophysical parameters.

    PubMed

    Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong

    2016-05-30

    Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.

  15. Catchment Area Treatment (CAT) Plan and Crop Area Optimization for Integrated Management in a Water Resource Project

    NASA Astrophysics Data System (ADS)

    Jaiswal, R. K.; Thomas, T.; Galkate, R. V.; Ghosh, N. C.; Singh, S.

    2013-09-01

    A scientifically developed catchment area treatment (CAT) plan and optimized pattern of crop areas may be the key for sustainable development of water resource, profitability in agriculture and improvement of overall economy in drought affected Bundelkhand region of Madhya Pradesh (India). In this study, an attempt has been made to develop a CAT plan using spatial variation of geology, geomorphology, soil, drainage, land use in geographical information system for selection of soil and water conservation measures and crop area optimization using linear programming for maximization of return considering water availability, area affinity, fertilizers, social and market constraints in Benisagar reservoir project of Chhatarpur district (M.P.). The scientifically developed CAT plan based on overlaying of spatial information consists of 58 mechanical measure (49 boulder bunds, 1 check dam, 7 cully plug and 1 percolation tank), 2.60 km2 land for agro forestry, 2.08 km2 land for afforestation in Benisagar dam and 67 mechanical measures (45 boulder bunds and 22 gully plugs), 7.79 km2 land for agro forestry, 5.24 km2 land for afforestation in Beniganj weir catchment with various agronomic measures for agriculture areas. The linear programming has been used for optimization of crop areas in Benisagar command for sustainable development considering various scenarios of water availability, efficiencies, affinity and fertilizers availability in the command. Considering present supply condition of water, fertilizers, area affinity and making command self sufficient in most of crops, the net benefit can be increase to Rs. 1.93 crores from 41.70 km2 irrigable area in Benisagar command by optimizing cropping pattern and reducing losses during conveyance and application of water.

  16. Methods of extending crop signatures from one area to another

    NASA Technical Reports Server (NTRS)

    Minter, T. C. (Principal Investigator)

    1979-01-01

    Efforts to develop a technology for signature extension during LACIE phases 1 and 2 are described. A number of haze and Sun angle correction procedures were developed and tested. These included the ROOSTER and OSCAR cluster-matching algorithms and their modifications, the MLEST and UHMLE maximum likelihood estimation procedures, and the ATCOR procedure. All these algorithms were tested on simulated data and consecutive-day LANDSAT imagery. The ATCOR, OSCAR, and MLEST algorithms were also tested for their capability to geographically extend signatures using LANDSAT imagery.

  17. An operational model to estimate hourly and daily crop evapotranspiration in hilly terrain: validation on wheat and oat crops

    NASA Astrophysics Data System (ADS)

    Rana, Gianfranco; Katerji, Nader; Ferrara, Rossana M.; Martinelli, Nicola

    2011-03-01

    In this paper, we present an operational model to estimate the actual evapotranspiration (ET) of crops cultivated on hilly terrains. This new model has the following three characteristics: (1) ET modelling is based on a Penman-Monteith (PM) type equation (Monteith 1965) where canopy resistance is simulated by following an approach already illustrated by Katerji and Perrier (Agronomie 3(6):513-521, 1983); (2) the estimation of ET, by means of the PM equation, is made by using meteorological variables simulated on sloped sites as input; (3) these variables are simulated by using simple relationships linking the variables measured at a reference site on plane to the topographic characteristics of the site (slope, orientation, altitude as difference between reference, and sloped sites). This approach presents two advantages if compared with previously proposed models: Not only computation steps are greatly simplified but also error sources due to the simulation of climatic variables in sloped sites and the ET estimation are well distinguished. This model was validated at hourly and daily scales at four sites cultivated with wheat and oats offering a wide range of slope and orientation values: a reference site on plane, site 1 (9° sloping, NW orientation, 7 m from the reference site in plane), site 2 (6°, SE, 12 m) and site 3 (1°, SE, 18 m). At hourly scale, the new model performed well at all sites studied. The observed slope of the linear relationships between estimated and measured ET values ranged between 0.93 and 1.03, with coefficients of determination, r 2, between 0.80 and 0.98. At daily scale, the slopes of the linear relationships between measured and estimated ET for the sites on plane and the sloped sites were practically the same (0.98 ± 0.01); however, the coefficient of determination r 2 observed in the site on plane was clearly greater (0.98) than that observed in the sloped sites (0.83). The presented analysis does not show any significant

  18. A Study of Estimating Winter Wheat Yields by Using Satellite Data Assimilation with Crop Growth Model

    NASA Astrophysics Data System (ADS)

    Kuwata, K.

    2013-12-01

    Accurate information of crop yield is important for production planning in agriculture. Crop growth model is a effective tool to comprehend crop growth situation. Accordingly, we use the MOSIS data for two types of utilization to provide necessary information for DSSAT. The objective of this study is developing a method of estimating winter wheat yield without adequate information of the field. The first use is estimation of solar radiation, which is required as input data into DSSAT. Since MODIS is observing the earth everyday, solar radiation can be estimated in a region where a climate observation system is not developed. The second use is data assimilation that provides appropriate parameter of cultivation management to DSSAT. MODIS LAI and Dry Matter Production (DMP) estimated from MODIS GPP are assimilated into DSSAT. Before developing data assimilation, we have accomplished sensitivity analysis of DSSAT. As the result of the analysis, we found that planting date and amount of applied fertilizer have correlated strongly with LAI and Dry Matter (DM) for specific growth period. Based on the result, we estimated winter wheat yield by assimilating MODIS LAI and DMP observed during the specific period. In contrast, previous study estimated crop yield by assimilating satellite data observed for the whole growth period. Three different assimilation schemes were tested to verify the accuracy of our method. Our results showed that the estimated winter wheat yield agreed very well with the Japanese agricultural experiment station data. Among different assimilating scenarios, the best result was obtained when MODIS LAI and DMP observed for specific growth period; the Root Square Mean Error (RMSE) was 406.52 kg ha2. The distribution map of full year incident PAR in Asia. Estimated Winter Wheat Yield in Japan In the case 1, detail information gathered by experiment reports.In the case 2, all management parameters are determined by reference to cultivation manuals.In the

  19. Remote estimation of gross primary productivity in crops: from close range to satellite observations

    NASA Astrophysics Data System (ADS)

    Peng, Y.; Gitelson, A. A.; Sakamoto, T.; Masek, J. G.; Rundquist, D.; Nguy-Robertson, A. L.; Verma, S.; Suyker, A.

    2013-12-01

    An accurate estimation of crop gross primary productivity (GPP) is essential for monitoring regional and global carbon exchanges. In this study, with ten-year observations throughout 2001 to 2010 at three irrigated and rainfed AmerFlux sites in Mead, Nebraska, a simple model was tested to estimate crop GPP using a product of chlorophyll-related vegetation index and photosynthetically active radiation (PAR). Vegetation indices (VI), a proxy of canopy chlorophyll, were calculated from canopy reflectance at various spatial and temporal resolution, including daily observations of four-band radiance 6 m above the ground, weekly in-situ measurements of hyperspectral reflectance, and satellite data (Landsat and MODIS). This model was able to estimate GPP accurately in croplands with different crop species, field managements and climatic conditions. It showed that the used VI was quite sensitive to detect daily GPP variation in crops even under stressed conditions when total Chl content is closely tied to seasonal dynamic of GPP. To minimize the uncertainty of GPP variations, which do not follow fluctuations of incoming PAR, potential PAR was introduced into the model as a better representative of radiation absorbed by canopy for photosynthesis. The model using satellite data and potential PAR is entirely based on remotely sensed data not requiring any ground-based observation. The indices using green and NIR Landsat bands were found to be the most accurate in GPP estimation with coefficients of variation below 13% for maize and 15% for soybean. Using MODIS 250 m data, EVI2 and WDRVI were accurate estimating GPP with coefficient of variation below 20% in maize and 25% in soybean.

  20. Light- and water-use efficiency model synergy: a revised look at crop yield estimation for agricultural decision-making

    NASA Astrophysics Data System (ADS)

    Marshall, M.; Tu, K. P.

    2015-12-01

    Large-area crop yield models (LACMs) are commonly employed to address climate-driven changes in crop yield and inform policy makers concerned with climate change adaptation. Production efficiency models (PEMs), a class of LACMs that rely on the conservative response of carbon assimilation to incoming solar radiation absorbed by a crop contingent on environmental conditions, have increasingly been used over large areas with remote sensing spectral information to improve the spatial resolution of crop yield estimates and address important data gaps. Here, we present a new PEM that combines model principles from the remote sensing-based crop yield and evapotranspiration (ET) model literature. One of the major limitations of PEMs is that they are evaluated using data restricted in both space and time. To overcome this obstacle, we first validated the model using 2009-2014 eddy covariance flux tower Gross Primary Production data in a rice field in the Central Valley of California- a critical agro-ecosystem of the United States. This evaluation yielded a Willmot's D and mean absolute error of 0.81 and 5.24 g CO2/d, respectively, using CO2, leaf area, temperature, and moisture constraints from the MOD16 ET model, Priestley-Taylor ET model, and the Global Production Efficiency Model (GLOPEM). A Monte Carlo simulation revealed that the model was most sensitive to the Enhanced Vegetation Index (EVI) input, followed by Photosynthetically Active Radiation, vapor pressure deficit, and air temperature. The model will now be evaluated using 30 x 30m (Landsat resolution) biomass transects developed in 2011 and 2012 from spectroradiometric and other non-destructive in situ metrics for several cotton, maize, and rice fields across the Central Valley. Finally, the model will be driven by Daymet and MODIS data over the entire State of California and compared with county-level crop yield statistics. It is anticipated that the new model will facilitate agro-climatic decision-making in

  1. An assessment of Landsat data acquisition history on identification and area estimation of corn and soybeans

    USGS Publications Warehouse

    Hixson, M. M.; Bauer, M. E.; Scholz, Donna K.

    1982-01-01

    In the past decade, numerous studies have demonstrated the potential of satellite remote sensing for providing accurate timely crop area information. This study assessed the impact of Landsat data acquisition history on classification and area estimation accuracy of corn and soybeans in the U.S. Corn Belt. The results illustrate the importance of selecting Landsat acquisitions based on spectral differences in crops at certain development stages. Although early season information can provide estimates of total corn and soybean areas, acquisitions from about emergence and after tasseling of the corn seem to provide a minimal set for accurate identification of corn and soybeans in the U.S. Corn Belt. Additional acquisitions provide only marginally greater separability for corn and soybeans.

  2. The estimation of rice paddy yield with GRAMI crop model and Geostationary Ocean Color Imager (GOCI) image over South Korea

    NASA Astrophysics Data System (ADS)

    Yeom, J. M.; Kim, H. O.

    2014-12-01

    In this study, we estimated the rice paddy yield with moderate geostationary satellite based vegetation products and GRAMI model over South Korea. Rice is the most popular staple food for Asian people. In addition, the effects of climate change are getting stronger especially in Asian region, where the most of rice are cultivated. Therefore, accurate and timely prediction of rice yield is one of the most important to accomplish food security and to prepare natural disasters such as crop defoliation, drought, and pest infestation. In the present study, GOCI, which is world first Geostationary Ocean Color Image, was used for estimating temporal vegetation indices of the rice paddy by adopting atmospheric correction BRDF modeling. For the atmospheric correction with LUT method based on Second Simulation of the Satellite Signal in the Solar Spectrum (6S), MODIS atmospheric products such as MOD04, MOD05, MOD07 from NASA's Earth Observing System Data and Information System (EOSDIS) were used. In order to correct the surface anisotropy effect, Ross-Thick Li-Sparse Reciprocal (RTLSR) BRDF model was performed at daily basis with 16day composite period. The estimated multi-temporal vegetation images was used for crop classification by using high resolution satellite images such as Rapideye, KOMPSAT-2 and KOMPSAT-3 to extract the proportional rice paddy area in corresponding a pixel of GOCI. In the case of GRAMI crop model, initial conditions are determined by performing every 2 weeks field works at Chonnam National University, Gwangju, Korea. The corrected GOCI vegetation products were incorporated with GRAMI model to predict rice yield estimation. The predicted rice yield was compared with field measurement of rice yield.

  3. Use of Sharpened Land Surface Temperature for Daily Evapotranspiration Estimation over Irrigated Crops in Arid Lands

    NASA Astrophysics Data System (ADS)

    Rosas Aguilar, J.; McCabe, M. F.; Houborg, R.; Gao, F.

    2014-12-01

    Satellite remote sensing provides data on land surface characteristics, useful for mapping land surface energy fluxes and evapotranspiration (ET). Land-surface temperature (LST) derived from thermal infrared (TIR) satellite data has been reliably used as a remote indicator of ET and surface moisture status. However, TIR imagery usually operates at a coarser resolution than that of shortwave sensors on the same satellite platform, making it sometimes unsuitable for monitoring of field-scale crop conditions. This study applies the data mining sharpener (DMS; Gao et al., 2012) technique to data from the Moderate Resolution Imaging Spectroradiometer (MODIS), which sharpens the 1 km thermal data down to the resolution of the optical data (250-500 m) based on functional LST and reflectance relationships established using a flexible regression tree approach. The DMS approach adopted here has been enhanced/refined for application over irrigated farming areas located in harsh desert environments in Saudi Arabia. The sharpened LST data is input to an integrated modeling system that uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI) in conjunction with model reanalysis data and remotely sensed data from polar orbiting (MODIS) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate daily estimates of evapotranspiration. Results are evaluated against available flux tower observations over irrigated maize near Riyadh in Saudi Arabia. Successful monitoring of field-scale changes in surface fluxes are of importance towards an efficient water use in areas where fresh water resources are scarce and poorly monitored. Gao, F.; Kustas, W.P.; Anderson, M.C. A Data Mining Approach for Sharpening Thermal Satellite Imagery over Land. Remote Sens. 2012, 4, 3287-3319.

  4. Utilization of Tum Nub (Embankment) for Expanding Double Rice Cropping Area in the Mekong Delta, Cambodia

    NASA Astrophysics Data System (ADS)

    Saito, Miho; Goto, Akira; Mizutani, Masakazu; Khem, Sothea

    This study aims to examine the effect of embankments for expanding double rice cropping area in the Cambodian Mekong Delta, where many traditional embankments called Tum Nub. For realizing double rice cropping in the flood plain, securing the cropping period and irrigation water during non-submerged days is essential, for which utilization of Tum Nub is considered to be effective. The field investigation revealed that some villages are practicing double rice cropping by introducing early rainy season rice. Hence, for introducing early rainy season rice, the effect of combination of two types of embankments was simulated for a target area selected: Type 1 embankment is making a reservoir for storing water, but single rice cropping is allowed in the inside of the reservoir after consuming stored water; and Type 2 is that for delaying the start of inundation. The result of the simulation showed that the combination of the embankments can increase rice production of the target area by 24-30% from the current level.

  5. Improving the S-Shape Solar Radiation Estimation Method for Supporting Crop Models

    PubMed Central

    Fodor, Nándor

    2012-01-01

    In line with the critical comments formulated in relation to the S-shape global solar radiation estimation method, the original formula was improved via a 5-step procedure. The improved method was compared to four-reference methods on a large North-American database. According to the investigated error indicators, the final 7-parameter S-shape method has the same or even better estimation efficiency than the original formula. The improved formula is able to provide radiation estimates with a particularly low error pattern index (PIdoy) which is especially important concerning the usability of the estimated radiation values in crop models. Using site-specific calibration, the radiation estimates of the improved S-shape method caused an average of 2.72 ± 1.02 (α = 0.05) relative error in the calculated biomass. Using only readily available site specific metadata the radiation estimates caused less than 5% relative error in the crop model calculations when they were used for locations in the middle, plain territories of the USA. PMID:22645451

  6. a Method to Estimate Temporal Interaction in a Conditional Random Field Based Approach for Crop Recognition

    NASA Astrophysics Data System (ADS)

    Diaz, P. M. A.; Feitosa, R. Q.; Sanches, I. D.; Costa, G. A. O. P.

    2016-06-01

    This paper presents a method to estimate the temporal interaction in a Conditional Random Field (CRF) based approach for crop recognition from multitemporal remote sensing image sequences. This approach models the phenology of different crop types as a CRF. Interaction potentials are assumed to depend only on the class labels of an image site at two consecutive epochs. In the proposed method, the estimation of temporal interaction parameters is considered as an optimization problem, whose goal is to find the transition matrix that maximizes the CRF performance, upon a set of labelled data. The objective functions underlying the optimization procedure can be formulated in terms of different accuracy metrics, such as overall and average class accuracy per crop or phenological stages. To validate the proposed approach, experiments were carried out upon a dataset consisting of 12 co-registered LANDSAT images of a region in southeast of Brazil. Pattern Search was used as the optimization algorithm. The experimental results demonstrated that the proposed method was able to substantially outperform estimates related to joint or conditional class transition probabilities, which rely on training samples.

  7. Assimilation of MODIS-derived LAI by radiative transfer modelling to crop growth simulation model for rice crop monitoring and yield estimation in the Mekong delta, Vietnam

    NASA Astrophysics Data System (ADS)

    Nguyen, H.; de Bie, K.; Verhoef, W.

    2014-12-01

    Successful monitoring of rice crops and estimation of its yields in Mekong delta provide vital information to government agencies, rice production stakeholders and insurance companies in making their decisions and plans to establish solutions to protect rice smallholders from the risks involved. Remote sensing-based information promises a cost-effective way to observe rice crop growth in the largest rice producing region of Vietnam. For an extensive rice cultivation region as the Mekong delta, the use of divergence statistic to extract information from long-term or hypertemporal optical remote sensing NDVI profile to map rice cropping patterns has shown a high degree of success. The result map provides accurate information on where rice grew, when it was seeded and harvested, how many time it was cultivated every year. In addition, by using 8-day MODIS TERRA surface reflectance in Soil-Leaf-Canopy (SLC) radiative transfer model, 70 percent variation of seasonal rice LAI values was able to capture, making it useful to be assimilated into a rice crop growth simulation model (ORYZA 2000) to estimate the regional rice production in the season of 2008-2009. Tested results from 56 rice fields located in different rice cropping patterns showed that yields estimated using ORYZA2000 can explain 83 percent variation of field measured yields. However, simulated yields by ORYZA 2000 were used to overestimate by the model since some of model parameters could not be recalibrated due to the lack of field experiment data. This suggest that in the future, in order to gain a better results of rice crop monitoring and yield estimation, apart from improving the estimation of MODIS -derived LAIs by using SLC, calibrating crop growth simulation's parameter have to be taken into account.

  8. Differences in CH4 and N2O emissions between rice nurseries in Chinese major rice cropping areas

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Li, Zhijie; Feng, Jinfei; Zhang, Xin; Jiang, Yu; Chen, Jin; Zhang, Mingqian; Deng, Aixing; Zhang, Weijian

    2014-10-01

    Studies on greenhouse gas (GHG) emissions from paddy field have primarily focused on the post-transplanting period, however, recent researches raise new concerns about GHGs emission from rice nursery. In this study, CH4 and N2O fluxes were determined from different nurseries under major rice cropping systems in China. The tested nurseries included flooded nursery (FN), moist nursery (MN) and dry nursery (DN). Methane emissions from FN were significantly higher than those from MN and DN under all the rice cropping systems. When comparing with FN, MN decreased total CH4 emissions by 74.2%, 72.1% and 49.6% under the rice-upland rotation cropping system (RUR), and the double rice cropping system for the early rice (EDR) and the late rice (LDR), respectively. DN decreased CH4 emissions by 99.2%, 92.0%, 99.0% and 78.6% compared to FN under the single rice cropping system (SR), RUR, EDR and LDR, respectively. When comparing with FN, MN and DN increased N2O emissions by 58.1-134.1% and 28.2-332.7%, respectively. Ultimately, compared with FN across the cropping systems, MN and DN decreased net global warming potentials (GWPs) of CH4 and N2O by 33-68% and 43-86%, respectively. The mitigating effect of MN and DN on total GWPs varied greatly across the systems, ranging from 30.8% in the LDR to 86.5% in the SR. Chinese actual emission from rice nurseries was reduced to 956.66 × 103 t CO2 eq from the theoretical estimate of 2242.59 × 103 t CO2 eq if under the flooded nursery scenario in 2012. Taking into account the large rice nursery area (2032.52 × 103 ha) in China, the results of this study clearly indicate the importance to estimate and mitigate GHGs emission from flooded rice nursery. Being effective to reduce GHG emissions and increase rice yield, dry nursery technique is a promising candidate for climate smart rice cropping.

  9. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  10. Estimation of runoff mitigation by morphologically different cover crop root systems

    NASA Astrophysics Data System (ADS)

    Yu, Yang; Loiskandl, Willibald; Kaul, Hans-Peter; Himmelbauer, Margarita; Wei, Wei; Chen, Liding; Bodner, Gernot

    2016-07-01

    Hydrology is a major driver of biogeochemical processes underlying the distinct productivity of different biomes, including agricultural plantations. Understanding factors governing water fluxes in soil is therefore a key target for hydrological management. Our aim was to investigate changes in soil hydraulic conductivity driven by morphologically different root systems of cover crops and their impact on surface runoff. Root systems of twelve cover crop species were characterized and the corresponding hydraulic conductivity was measured by tension infiltrometry. Relations of root traits to Gardner's hydraulic conductivity function were determined and the impact on surface runoff was estimated using HYDRUS 2D. The species differed in both rooting density and root axes thickness, with legumes distinguished by coarser axes. Soil hydraulic conductivity was changed particularly in the plant row where roots are concentrated. Specific root length and median root radius were the best predictors for hydraulic conductivity changes. For an intensive rainfall simulation scenario up to 17% less rainfall was lost by surface runoff in case of the coarsely rooted legumes Melilotus officinalis and Lathyrus sativus, and the densely rooted Linum usitatissimum. Cover crops with coarse root axes and high rooting density enhance soil hydraulic conductivity and effectively reduce surface runoff. An appropriate functional root description can contribute to targeted cover crop selection for efficient runoff mitigation.

  11. Estimated crop yield losses due to surface ozone exposure and economic damage in India.

    PubMed

    Debaje, S B

    2014-06-01

    In this study, we estimate yield losses and economic damage of two major crops (winter wheat and rabi rice) due to surface ozone (O3) exposure using hourly O3 concentrations for the period 2002-2007 in India. This study estimates crop yield losses according to two indices of O3 exposure: 7-h seasonal daytime (0900-1600 hours) mean measured O3 concentration (M7) and AOT40 (accumulation exposure of O3 concentration over a threshold of 40 parts per billion by volume during daylight hours (0700-1800 hours), established by field studies. Our results indicate that relative yield loss from 5 to 11% (6-30%) for winter wheat and 3-6% (9-16%) for rabi rice using M7 (AOT40) index of the mean total winter wheat 81 million metric tons (Mt) and rabi rice 12 Mt production per year for the period 2002-2007. The estimated mean crop production loss (CPL) for winter wheat are from 9 to 29 Mt, account for economic cost loss was from 1,222 to 4,091 million US$ annually. Similarly, the mean CPL for rabi rice are from 0.64 to 2.1 Mt, worth 86-276 million US$. Our calculated winter wheat and rabi rice losses agree well with previous results, providing the further evidence that large crop yield losses occurring in India due to current O3 concentration and further elevated O3 concentration in future may pose threat to food security.

  12. Updating small area population estimates in England and Wales.

    PubMed

    Simpson, S; Diamond, I; Tonkin, P; Tye, R

    1996-01-01

    "Population estimates have important implications for resource allocation within government and commerce, and are often assumed to be without error. Currently, central government provides annual population estimates for all the local and health authority districts in Britain, but estimates are needed for smaller areas, typically for electoral wards and postal sectors. Small area estimates are provided by some local authorities and commercial organizations, using different methods; the accuracy of these estimates is modelled here within a multilevel framework. Certain characteristics of the small area and of the method of estimation are included as explanatory variables. Results show that the method of estimation used is of great importance."

  13. Impacts of Reprojection and Sampling of MODIS Satellite Images on Estimating Crop Evapotranspiration Using METRIC model

    NASA Astrophysics Data System (ADS)

    Pun, M.; Kilic, A.; Allen, R.

    2014-12-01

    Landsat satellite images have been used frequently to map evapotranspiration (ET) andbiophysical variables at the field scale with surface energy balance algorithms. Although Landsat images have high spatial resolution with 30m cell size, it has limitations for real time monitoring of crop ET by providing only two to four images per month for an area, which, when encountered with cloudy days, further deteriorates the availability of images and snapshots of ET behavior. Therefore real time monitoring essentially has to include near-daily thermal satellites such as MODIS/VIIRS into the time series. However, the challenge with field scale monitoring with these systems is the large size of the thermal band which is 375 m with VIIRS and 1000 meter with MODIS. To maximize the accuracy of ET estimates during infusion of MODIS products into land surface models for monitoring field scale ET, it is important to assess the geometric accuracy of the various MODIS products, for example, spatial correspondence among the 250 m red and near-infrared bands, the 500 m reflectance bands; and the 1000 m thermal bands and associated products. METRIC model was used with MODIS images to estimate ET from irrigated and rainfed fields in Nebraska. Our objective was to assess geometric accuracy of MODIS image layers and how to correctly handle these data for highest accuracy of estimated ET at the individual field scale during the extensive drought of 2012. For example, the particular tool used to subset and reproject MODIS swath images from level-1 and level-2 products (e.g., using the MRTSwath and other tools), the initial starting location (upper left hand corner), and the projection system all effect how pixel corners of the various resolution bands align. Depending on the approach used, origin of pixel corners can vary from image to image date and therefore impacts the pairing of ET information from multiple dates the consistency and accuracy of sampling ET from within field interiors

  14. Crop suitability monitoring for improved yield estimations with 100m PROBA-V data

    NASA Astrophysics Data System (ADS)

    Özüm Durgun, Yetkin; Gilliams, Sven; Gobin, Anne; Duveiller, Grégory; Djaby, Bakary; Tychon, Bernard

    2015-04-01

    This study has been realised within the framework of a PhD targeting to advance agricultural monitoring with improved yield estimations using SPOT VEGETATION remotely sensed data. For the first research question, the aim was to improve dry matter productivity (DMP) for C3 and C4 plants by adding a water stress factor. Additionally, the relation between the actual crop yield and DMP was studied. One of the limitations was the lack of crop specific maps which leads to the second research question on 'crop suitability monitoring'. The objective of this work is to create a methodological approach based on the spectral and temporal characteristics of PROBA-V images and ancillary data such as meteorology, soil and topographic data to improve the estimation of annual crop yields. The PROBA-V satellite was launched on 6th May 2013, and was designed to bridge the gap in space-borne vegetation measurements between SPOT-VGT (March 1998 - May 2014) and the upcoming Sentinel-3 satellites scheduled for launch in 2015/2016. PROBA -V has products in four spectral bands: BLUE (centred at 0.463 µm), RED (0.655 µm), NIR (0.845 µm), and SWIR (1.600 µm) with a spatial resolution ranging from 1km to 300m. Due to the construction of the sensor, the central camera can provide a 100m data product with a 5 to 8 days revisiting time. Although the 100m data product is still in test phase a methodology for crop suitability monitoring was developed. The multi-spectral composites, NDVI (Normalised Difference Vegetation Index) (NIR_RED/NIR+RED) and NDII (Normalised Difference Infrared Index) (NIR-SWIR/NIR+SWIR) profiles are used in addition to secondary data such as digital elevation data, precipitation, temperature, soil types and administrative boundaries to improve the accuracy of crop yield estimations. The methodology is evaluated on several FP7 SIGMA test sites for the 2014 - 2015 period. Reference data in the form of vector GIS with boundaries and cover type of agricultural fields are

  15. Kohonen self-organizing map estimator for the reference crop evapotranspiration

    NASA Astrophysics Data System (ADS)

    Adeloye, Adebayo J.; Rustum, Rabee; Kariyama, Ibrahim D.

    2011-08-01

    Reference crop evapotranspiration (ETo) estimation is of importance in irrigation water management for the calculation of crop water requirements and its scheduling, in rainfall-runoff modeling and in numerous other water resources studies. Due to its importance, several direct and indirect methods have been employed to determine the reference crop evapotranspiration but success has been limited because the direct measurement methods lack in precision and accuracy due to scale issues and other problems, while some of the more accurate indirect methods, e.g., the Penman-Monteith benchmark model, are time-consuming and require weather input data that are not routinely monitored. This paper has used the Kohonen self-organizing map (KSOM), unsupervised artificial neural networks, to predict the ETo. based on observed daily weather data at two climatically diverse basins: a small experimental catchment in temperate Edinburgh, UK and a semiarid lake basin in Udaipur, India. This was achieved by using the powerful clustering capability of the KSOM to analyze the multidimensional data array comprising the estimated ETo (based on the Food and Agricultural Organization (FAO) Penman-Monteith model) and different subsets of climatic variables known to affect it. The findings indicate that the KSOM-based ETo estimates even with fewer input variables were in good agreement with those obtained using the conventional FAO Penman-Monteith formulation employing the full complement of weather data at the two locations. More crucially, the KSOM-based estimates were also found to be significantly superior to those estimated using currently recommended empirical ETo methods for data scarce situations such as those in developing countries.

  16. FARM WORKERS IN A SPECIALIZED SEASONAL CROP AREA, STANISLAUS COUNTY, CALIFORNIA.

    ERIC Educational Resources Information Center

    METZLER, WILLIAM H.

    SPECIALIZATION IN THE CROPS BEST ADAPTED TO THE LOCAL AREA IS SEEN AS A HIGHLY PRODUCTIVE SYSTEM OF AGRICULTURE, BUT BY CREATING THE NEED FOR LARGE NUMBERS OF WORKERS FOR SHORT PERIODS OF TIME, IT CAUSES UNEMPLOYMENT AND MIGRATION. A SURVEY OF FRUIT AND VEGETABLE WORKERS IN STANISLAUS COUNTY, CALIFORNIA IN 1962-63 REVEALS--(1) THEIR EARNINGS ARE…

  17. Copper and lead levels in crops and soils of the Holland Marsh Area-Ontario

    SciTech Connect

    Czuba, M.; Hutchinson, T.C.

    1980-01-01

    A study was made of the occurrence, distribution, and concentrations of the heavy metals copper (Cu) and lead (Pb) in the soils and crops of the important horticultural area north of Toronto known as the Holland Marsh. The soils are deep organic mucks (> 85% organic matter), derived by the drainage of black marshland soils, which has been carried out over the past 40 years. A comparison is made between the Pb and Cu concentrations in undrained, uncultivated areas of the marsh and in the intensively used horticultural area. Analyses show a marked accumulation of Cu in surface layers of cultivated soils, with a mean surface concentration of 130 ppM, declining to 20 ppM at a 32-cm depth. Undrained (virgin) soils of the same marshes had < 20 ppM at all depths. Lead concentrations also declined through the profile, from concentrations of 22 to 10 ppM. In comparison, undrained areas had elevated Pb levels. Cultivation appeared to have increased Cu, but lowered Pb in the marsh. Copper and lead levels found in the crops were generally higher in the young spring vegetables than in the mature fall ones. Leafy crops, especially lettuce (Lactuca L.) and celery (Apium graveolens), accumulated higher Pb levels in their foliage compared with levels in root crops. Cultivation procedures, including past pesticide applications and fertilizer additions, appeared to be principal sources of Cu. Mobility from the soil and into the plant for these elements in the marsh muck soils is discussed.

  18. Productivity and carbon dioxide exchange of leguminous crops: estimates from flux tower measurements

    USGS Publications Warehouse

    Gilmanov, Tagir G.; Baker, John M.; Bernacchi, Carl J.; Billesbach, David P.; Burba, George G.; Castro, Saulo; Chen, Jiquan; Eugster, Werner; Fischer, Marc L.; Gamon, John A.; Gebremedhin, Maheteme T.; Glenn, Aaron J.; Griffis, Timothy J.; Hatfield, Jerry L.; Heuer, Mark W.; Howard, Daniel M.; Leclerc, Monique Y.; Loescher, Henry W.; Marloie, Oliver; Meyers, Tilden P.; Olioso, Albert; Phillips, Rebecca L.; Prueger, John H.; Skinner, R. Howard; Suyker, Andrew E.; Tenuta, Mario; Wylie, Bruce K.

    2014-01-01

    Net CO2 exchange data of legume crops at 17 flux tower sites in North America and three sites in Europe representing 29 site-years of measurements were partitioned into gross photosynthesis and ecosystem respiration by using the nonrectangular hyperbolic light-response function method. The analyses produced net CO2 exchange data and new ecosystem-scale ecophysiological parameter estimates for legume crops determined at diurnal and weekly time steps. Dynamics and annual totals of gross photosynthesis, ecosystem respiration, and net ecosystem production were calculated by gap filling with multivariate nonlinear regression. Comparison with the data from grain crops obtained with the same method demonstrated that CO2 exchange rates and ecophysiological parameters of legumes were lower than those of maize (Zea mays L.) but higher than for wheat (Triticum aestivum L.) crops. Year-round annual legume crops demonstrated a broad range of net ecosystem production, from sinks of 760 g CO2 m–2 yr–1 to sources of –2100 g CO2 m–2 yr–1, with an average of –330 g CO2 m–2 yr–1, indicating overall moderate CO2–source activity related to a shorter period of photosynthetic uptake and metabolic costs of N2 fixation. Perennial legumes (alfalfa, Medicago sativa L.) were strong sinks for atmospheric CO2, with an average net ecosystem production of 980 (range 550–1200) g CO2 m–2 yr–1.

  19. The Tasseled Cap Transformation for RapidEye data and the estimation of vital and senescent crop parameters

    NASA Astrophysics Data System (ADS)

    Schonert, M.; Zillmann, E.; Weichelt, H.; Eitel, J. U. H.; Magney, T. S.; Lilienthal, H.; Siegmann, B.; Jarmer, T.

    2015-04-01

    The retrieval of crop biophysical parameters using spectral indices obtained from high temporal and spatial resolution satellite data, is a valuable tool to monitor crop growth and status. Tasseled Cap Features (TCFs) for RapidEye data were derived from spectral variances typically present in agricultural scenes. The TCF Greenness (GRE) was aligned to the spectral variance of vital vegetation, and therefore, it represents the typical reflectance characteristics of green vegetation, with relatively higher reflectance at the nearinfrared (NIR) range. The TCF Yellowness (YEL) was aligned to correspond to the reflectance characteristics of senescent crops, with relatively higher reflectance in the visible portion of the spectrum due to chlorophyll breakdown, and lower reflectance in the NIR range due to cell structure decomposition compared to vital green vegetation. The goal of this work was to assess the potential of RapidEye's TCFs for the prediction of green leaf area index (LAI), plant chlorophyll (Chl), and nitrogen (N) concentration, as well as the identification of senescence patterns. The linear relationships between the biophysical parameters and the TCFs were compared to the performance of the widely used indices NDVI and PSRI. Preliminary results indicate that GRE is strongly related to LAI in vital crops and suggests a higher predictive power than NDVI. YEL demonstrated a strong linear relation and a higher potential to estimate Chl and N concentration in senescent soft white winter wheat (Triticum aestivum L.) in comparison to PSRI. PSRI showed a stronger correlation to Chl in senescent soft white spring wheat (Triticum aestivum L.), compared to YEL. Results indicate that YEL may be used to characterize the variability in senescence status within fields. This information, in conjunction with soil fertility and yield maps, can potentially be used to designate precision management zones.

  20. Development of rotation sample designs for the estimation of crop acreages

    NASA Technical Reports Server (NTRS)

    Lycthuan-Lee, T. G. (Principal Investigator)

    1981-01-01

    The idea behind the use of rotation sample designs is that the variation of the crop acreage of a particular sample unit from year to year is usually less than the variation of crop acreage between units within a particular year. The estimation theory is based on an additive mixed analysis of variance model with years as fixed effects, (a sub t), and sample units as a variable factor. The rotation patterns are decided upon according to: (1) the number of sample units in the design each year; (2) the number of units retained in the following years; and (3) the number of years to complete the rotation pattern. Different analytic formulae for the variance of (a sub t) and the variance comparisons in using a complete survey of the rotation patterns.

  1. Soybean Area and Yield Estimation Using MODIS and Landsat Data in the Conterminous United States

    NASA Astrophysics Data System (ADS)

    Song, X. P.; Hansen, M.; Potapov, P.; Stehman, S. V.; Krylov, A.; King, L.; Adusei, B.

    2015-12-01

    The world's population is projected to grow to 9 billion by 2050. The increasing population, amplified by people's increasing consumption of animal products will create a massive demand for food and feed from grain production. As such, global food security will remain a worldwide concern for the next half century. Addressing the food security issue requires data and information support, including research and operational programs for crop monitoring, modeling and yield forecasting. Satellite observations, owing to their synoptic and repetitive nature, have the unique advantage of providing timely information on crop growth at regional to global scales. However, it remains a challenge to accurately identify crop type, estimate areal extent and forecast crop yield with satellite data. Here we employ a stratified random sampling framework for estimating soybean area and yield in the conterminous United States using satellite data collected by the MODIS and Landsat sensors. Complementing each other, the temporally-rich MODIS data are used to capture rapid phenological transitions of soybean crops, whereas the moderate-resolution Landsat data are used to delineate more spatial details for accurate area estimation. For every sample, we derive generic phenological metrics from MODIS and Landsat data and employ machine learning algorithms to identify soybean pixels with reference data generated from RapidEye images and verified by extensive field visits. We also characterize empirical relationships between satellite metrics and soybean yield compiled by the USDA National Agricultural Statistics Service (NASS). Preliminary results suggest that MODIS data alone underestimate soybean area considerably, whereas Landsat data can provide accurate estimate on soybean area. However, soybean yield can be predicted using MODIS-based reflectance metrics. Our sample depict well the spatial variation of soybean yield over the conterminous United States. In addition, the area

  2. Towards a Quantitative Use of Satellite Remote Sensing in Crop Growth Models for Large Scale Agricultural Production Estimate (Invited)

    NASA Astrophysics Data System (ADS)

    Defourny, P.

    2013-12-01

    The development of better agricultural monitoring capabilities is clearly considered as a critical step for strengthening food production information and market transparency thanks to timely information about crop status, crop area and yield forecasts. The documentation of global production will contribute to tackle price volatility by allowing local, national and international operators to make decisions and anticipate market trends with reduced uncertainty. Several operational agricultural monitoring systems are currently operating at national and international scales. Most are based on the methods derived from the pioneering experiences completed some decades ago, and use remote sensing to qualitatively compare one year to the others to estimate the risks of deviation from a normal year. The GEO Agricultural Monitoring Community of Practice described the current monitoring capabilities at the national and global levels. An overall diagram summarized the diverse relationships between satellite EO and agriculture information. There is now a large gap between the current operational large scale systems and the scientific state of the art in crop remote sensing, probably because the latter mainly focused on local studies. The poor availability of suitable in-situ and satellite data over extended areas hampers large scale demonstrations preventing the much needed up scaling research effort. For the cropland extent, this paper reports a recent research achievement using the full ENVISAT MERIS 300 m archive in the context of the ESA Climate Change Initiative. A flexible combination of classification methods depending to the region of the world allows mapping the land cover as well as the global croplands at 300 m for the period 2008 2012. This wall to wall product is then compared with regards to the FP 7-Geoland 2 results obtained using as Landsat-based sampling strategy over the IGADD countries. On the other hand, the vegetation indices and the biophysical variables

  3. Influence of resolution in irrigated area mapping and area estimation

    USGS Publications Warehouse

    Velpuri, N.M.; Thenkabail, P.S.; Gumma, M.K.; Biradar, C.; Dheeravath, V.; Noojipady, P.; Yuanjie, L.

    2009-01-01

    The overarching goal of this paper was to determine how irrigated areas change with resolution (or scale) of imagery. Specific objectives investigated were to (a) map irrigated areas using four distinct spatial resolutions (or scales), (b) determine how irrigated areas change with resolutions, and (c) establish the causes of differences in resolution-based irrigated areas. The study was conducted in the very large Krishna River basin (India), which has a high degree of formal contiguous, and informal fragmented irrigated areas. The irrigated areas were mapped using satellite sensor data at four distinct resolutions: (a) NOAA AVHRR Pathfinder 10,000 m, (b) Terra MODIS 500 m, (c) Terra MODIS 250 m, and (d) Landsat ETM+ 30 m. The proportion of irrigated areas relative to Landsat 30 m derived irrigated areas (9.36 million hectares for the Krishna basin) were (a) 95 percent using MODIS 250 m, (b) 93 percent using MODIS 500 m, and (c) 86 percent using AVHRR 10,000 m. In this study, it was found that the precise location of the irrigated areas were better established using finer spatial resolution data. A strong relationship (R2 = 0.74 to 0.95) was observed between irrigated areas determined using various resolutions. This study proved the hypotheses that "the finer the spatial resolution of the sensor used, greater was the irrigated area derived," since at finer spatial resolutions, fragmented areas are detected better. Accuracies and errors were established consistently for three classes (surface water irrigated, ground water/conjunctive use irrigated, and nonirrigated) across the four resolutions mentioned above. The results showed that the Landsat data provided significantly higher overall accuracies (84 percent) when compared to MODIS 500 m (77 percent), MODIS 250 m (79 percent), and AVHRR 10,000 m (63 percent). ?? 2009 American Society for Photogrammetry and Remote Sensing.

  4. The Importance of Rotational Crops for Biodiversity Conservation in Mediterranean Areas

    PubMed Central

    Chiatante, Gianpasquale; Meriggi, Alberto

    2016-01-01

    Nowadays we are seeing the largest biodiversity loss since the extinction of the dinosaurs. To conserve biodiversity it is essential to plan protected areas using a prioritization approach, which takes into account the current biodiversity value of the sites. Considering that in the Mediterranean Basin the agro-ecosystems are one of the most important parts of the landscape, the conservation of crops is essential to biodiversity conservation. In the framework of agro-ecosystem conservation, farmland birds play an important role because of their representativeness, and because of their steady decline in the last Century in Western Europe. The main aim of this research was to define if crop dominated landscapes could be useful for biodiversity conservation in a Mediterranean area in which the landscape was modified by humans in the last thousand years and was affected by the important biogeographical phenomenon of peninsula effect. To assess this, we identify the hotspots and the coldspots of bird diversity in southern Italy both during the winter and in the breeding season. In particular we used a scoring method, defining a biodiversity value for each cell of a 1-km grid superimposed on the study area, using data collected by fieldwork following a stratified random sampling design. This value was analysed by a multiple linear regression analysis and was predicted in the whole study area. Then we defined the hotspots and the coldspots of the study area as 15% of the cells with higher and lower value of biodiversity, respectively. Finally, we used GAP analysis to compare hotspot distribution with the current network of protected areas. This study showed that the winter hotspots of bird diversity were associated with marshes and water bodies, shrublands, and irrigated crops, whilst the breeding hotspots were associated with more natural areas (e.g. transitional wood/shrubs), such as open areas (natural grasslands, pastures and not irrigated crops). Moreover, the

  5. The Importance of Rotational Crops for Biodiversity Conservation in Mediterranean Areas.

    PubMed

    Chiatante, Gianpasquale; Meriggi, Alberto

    2016-01-01

    Nowadays we are seeing the largest biodiversity loss since the extinction of the dinosaurs. To conserve biodiversity it is essential to plan protected areas using a prioritization approach, which takes into account the current biodiversity value of the sites. Considering that in the Mediterranean Basin the agro-ecosystems are one of the most important parts of the landscape, the conservation of crops is essential to biodiversity conservation. In the framework of agro-ecosystem conservation, farmland birds play an important role because of their representativeness, and because of their steady decline in the last Century in Western Europe. The main aim of this research was to define if crop dominated landscapes could be useful for biodiversity conservation in a Mediterranean area in which the landscape was modified by humans in the last thousand years and was affected by the important biogeographical phenomenon of peninsula effect. To assess this, we identify the hotspots and the coldspots of bird diversity in southern Italy both during the winter and in the breeding season. In particular we used a scoring method, defining a biodiversity value for each cell of a 1-km grid superimposed on the study area, using data collected by fieldwork following a stratified random sampling design. This value was analysed by a multiple linear regression analysis and was predicted in the whole study area. Then we defined the hotspots and the coldspots of the study area as 15% of the cells with higher and lower value of biodiversity, respectively. Finally, we used GAP analysis to compare hotspot distribution with the current network of protected areas. This study showed that the winter hotspots of bird diversity were associated with marshes and water bodies, shrublands, and irrigated crops, whilst the breeding hotspots were associated with more natural areas (e.g. transitional wood/shrubs), such as open areas (natural grasslands, pastures and not irrigated crops). Moreover, the

  6. The Importance of Rotational Crops for Biodiversity Conservation in Mediterranean Areas.

    PubMed

    Chiatante, Gianpasquale; Meriggi, Alberto

    2016-01-01

    Nowadays we are seeing the largest biodiversity loss since the extinction of the dinosaurs. To conserve biodiversity it is essential to plan protected areas using a prioritization approach, which takes into account the current biodiversity value of the sites. Considering that in the Mediterranean Basin the agro-ecosystems are one of the most important parts of the landscape, the conservation of crops is essential to biodiversity conservation. In the framework of agro-ecosystem conservation, farmland birds play an important role because of their representativeness, and because of their steady decline in the last Century in Western Europe. The main aim of this research was to define if crop dominated landscapes could be useful for biodiversity conservation in a Mediterranean area in which the landscape was modified by humans in the last thousand years and was affected by the important biogeographical phenomenon of peninsula effect. To assess this, we identify the hotspots and the coldspots of bird diversity in southern Italy both during the winter and in the breeding season. In particular we used a scoring method, defining a biodiversity value for each cell of a 1-km grid superimposed on the study area, using data collected by fieldwork following a stratified random sampling design. This value was analysed by a multiple linear regression analysis and was predicted in the whole study area. Then we defined the hotspots and the coldspots of the study area as 15% of the cells with higher and lower value of biodiversity, respectively. Finally, we used GAP analysis to compare hotspot distribution with the current network of protected areas. This study showed that the winter hotspots of bird diversity were associated with marshes and water bodies, shrublands, and irrigated crops, whilst the breeding hotspots were associated with more natural areas (e.g. transitional wood/shrubs), such as open areas (natural grasslands, pastures and not irrigated crops). Moreover, the

  7. Application of SEBAL methodology for estimating and disseminating through third generation mobile phones crop water requirements in Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, G.; Hadjimitsis, M.; Perdikou, S.; Hadjimitsis, D.; Papadavid, C.; Neophtytou, N.; Kountios, G.; Michaelides, A.

    2013-08-01

    Water allocation to crops has always been of great importance in agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). Finally Crop Water Requirements derived from the specific research are disseminated to crop producers through a network of 3rd generation mobile phones.

  8. Estimating biomass, yield, evaprotranspiration and carbon fluxes for winter wheat by using high resolution remote sensing data combined with a crop model

    NASA Astrophysics Data System (ADS)

    Veloso, A.; Ceschia, E.; Demarez, V.

    2013-12-01

    The use of crop models allows simulating plant development, growth, yield, CO2 and water fluxes under different environmental and management conditions. When combined with high spatial and temporal resolution remote sensing data, these models provide new perspectives for crop monitoring at regional scale. Besides, monitoring spatial and temporal variation in water budget and amount of carbon fixed by these crops is an ultimate goal of earth climate change studies. We propose here an approach to estimate time courses of dry aboveground biomass (DAM), yield and evapotranspiration (ETR) for winter wheat by assimilating Green Area Index (GAI) data, obtained from satellite observations, into a simple crop model. This model is then coupled with a ';carbon flux module' for estimating the components of the carbon budget (gross primary production (GPP), ecosystem respiration (Reco), ...). Among the several land surface biophysical variables accessible from satellite observations, the GAI is the one that has a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Many methods have been developed to relate GAI to optical remote sensing signal. Here, seasonal dynamics of remotely sensed GAI were estimated by applying a method based on the inversion of a radiative transfer model using artificial neural networks. For this work, we employed a unique set of Formosat-2 and SPOT images acquired from 2006 to 2011 in southwest France. The modelling approach is based on the Simple Algorithm for Yield and Evapotranspiration estimate (SAFYE) model, which couples the FAO-56 model with an agro-meteorological model, based on Monteith's light-use efficiency theory. The SAFYE model is a daily time step crop model that simulates time series of GAI, biomass (NPP), grain yield and ETR. The carbon flux module simulates GPP, the autotrophic respiration (Ra) that is defined as the sum of plant growth and maintenance respiration and the heterotrophic respiration (Rh

  9. Small Area Income and Poverty Estimates (SAIPE): 2010 Highlights

    ERIC Educational Resources Information Center

    US Census Bureau, 2011

    2011-01-01

    This document presents 2010 data from the Small Area Income and Poverty Estimates (SAIPE) program of the U.S. Census Bureau. The SAIPE program produces poverty estimates for the total population and median household income estimates annually for all counties and states. SAIPE data also produces single-year poverty estimates for the school-age…

  10. Crop Coefficients of Some Selected Crops of Andhra Pradesh

    NASA Astrophysics Data System (ADS)

    Reddy, K. Chandrasekhar; Arunajyothy, S.; Mallikarjuna, P.

    2015-06-01

    Precise information on crop coefficients for estimating crop evapotranspiration (ETc) for regional scale irrigation planning is a major impediment in many regions. Crop coefficients suggested based on lysimeter data by earlier investigators have to be locally calibrated to account for the differences in the crop canopy under given climatic conditions. In the present study crop coefficients were derived based on reference crop evapotranspiration (ET0) estimated from Penman-Monteith equation and lysimeter measured ETc for groundnut, paddy, tobacco, sugarcane and castor crops at Tirupati, Nellore, Rajahmundry, Anakapalli and Rajendranagar centers of Andhra Pradesh respectively. Crop coefficients derived were compared with those recommended by FAO-56. The mean crop coefficients at different stages of growth were significantly different from those of FAO-56 curve though a similar trend was observed. A third order polynomial crop coefficient model has therefore been developed as a function of time (days after sowing the crop) for deriving suitable crop coefficients. The crop coefficient models suggested may be adopted to estimate crop evapotranspiration in the study area with reasonable degree of accuracy.

  11. Analyzing C-band SAR polarimetric information for LAI and crop yield estimations

    NASA Astrophysics Data System (ADS)

    Molijn, Ramses A.; Iannini, Lorenzo; Mousivand, Ali; Hanssen, Ramon F.

    2014-10-01

    In this study, space remote sensing data and crop specific information from the ESA-led AgriSAR 2009 campaign are used for studying the profiles of C-band SAR backscatter signals and multispectral-based leaf area index (LAI) over the growth period of canola, pea and wheat. In addition, the correlations between radar backscatter parameters and the crop yields were analyzed, based on extracted statistics of temporal profiles. The results show that the HV backscatter and LAI are correlated differently before and after LAI peak. In addition, the coefficient of determination between peakrelated statistics from polarimetric indicator profiles and yield for pea fields can reach up to 0.68, and for canola and wheat up to 0.47 and 0.5, respectively. HV backscatter and coherence between HH and VV are most.

  12. LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Optical remote sensing of crop nitrogen (N) status is developing into a powerful diagnostic tool that can improve N management decisions. Crop N status is a function of dry mass per unit area (W) and N concentration (%Na), which can be used to calculate N nutrition index (NNI),where NNI is %Na/%Nc (...

  13. Remote sensing applications for estimating changes on crop evapotranspiration of the most water intensive crops, due to climate change in Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, G.; Neocleous, D.; Stylianou, A.; Markou, M.; Kountios, G.; Hadjimitsis, D.

    2016-08-01

    Water allocation to crops, and especially to the most water intensive ones, has always been of great importance in agricultural process. Deficit or excess water irrigation quantities could create either crop health related problems or water over-consumption situation which lead to stored water reduction and toxic material depletion to deeper ground layers, respectively. In this context, and under the current conditions, where Cyprus is facing effects of climate changes, purpose of this study is basically to estimate the needed crop water requirements of the past (1995-2004) and the corresponding ones of the present (2005-2015) in order to test if there were any significant changes regarding the crop water requirements of the most water intensive trees in Cyprus. Mediterranean region has been identified as the region that will suffer the most from climate change. Thus the paper refers to effects of climate changes on crop evapotranspiration (ETc) using remotely sensed data from Landsat TM/ ETM+ / OLI employing a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL). Though the general feeling is that of changes on climate will consequently affect ETc, the results have indicated that there is no significant effect of climate change on crop evapotranspiration, despite the fact that some climatic factors have changed. Applying Student's T-test, the mean values for the most water intensive trees in Cyprus of the 1994-2004 decade have shown no statistical difference from the mean values of 2005-2015 decade's for all the cases, concluding that the climate change taking place the last decades in Cyprus have either not affected the crop evapotranspiration or the crops have manage to adapt into the new environmental conditions through time.

  14. A double-hurdle model estimation of cocoa farmers' willingness to pay for crop insurance in Ghana.

    PubMed

    Okoffo, Elvis Dartey; Denkyirah, Elisha Kwaku; Adu, Derick Taylor; Fosu-Mensah, Benedicta Yayra

    2016-01-01

    Agriculture is an important sector in Ghana's economy, however, with high risk due to natural factors like climate change, pests and diseases and bush fires among others. Farmers in the Brong-Ahafo region of Ghana which is known as one of the major cocoa producing regions, face these risks which sometimes results in crop failure. The need for farmers to therefore insure their farms against crop loss is crucial. Insurance has been a measure to guard against risk. The aim of this study was to assess cocoa farmers' willingness to access crop insurance, the factors affecting willingness to pay (WTP) for crop insurance scheme and insurance companies' willingness to provide crop insurance to cocoa farmers. Multi-stage sampling technique was used to sample 240 farmers from four communities in the Dormaa West District in Brong-Ahafo Region. The double-hurdle model shows that age, marital status and education significantly and positively influenced cocoa farmer's willingness to insure their farms whiles household size and cropped area negatively influenced farmers' willingness to insure their farms. Similarly, age, household size and cropped area significantly and positively influenced the premium cocoa farmers were willing to pay whiles marital status and cocoa income negatively influenced the premium farmers were willing to pay. The contingent valuation method shows that the maximum, minimum and average amounts cocoa farmers are willing to pay for crop insurance per production cost per acre was GH¢128.40, GH¢32.10 and GH¢49.32 respectively. Insurance companies do not have crop insurance policy but willing to provide crop insurance policy to cocoa farmers on a condition that farmers adopt modern cultivation practices to reduce the level of risk. The study recommends that cocoa farmers should be well educated on crop insurance and should be involved in planning the crop insurance scheme in order to conclude on the premium to be paid by them.

  15. Global Climate Niche Estimates for Bioenergy Crops and Invasive Species of Agronomic Origin: Potential Problems and Opportunities

    PubMed Central

    Barney, Jacob N.; DiTomaso, Joseph M.

    2011-01-01

    The global push towards a more biomass-based energy sector is ramping up efforts to adopt regionally appropriate high-yielding crops. As potential bioenergy crops are being moved around the world an assessment of the climatic suitability would be a prudent first step in identifying suitable areas of productivity and risk. Additionally, this assessment also provides a necessary step in evaluating the invasive potential of bioenergy crops, which present a possible negative externality to the bioeconomy. Therefore, we provide the first global climate niche assessment for the major graminaceous (9), herbaceous (3), and woody (4) bioenergy crops. Additionally, we contrast these with climate niche assessments for North American invasive species that were originally introduced for agronomic purposes as examples of well-intentioned introductions gone awry. With few exceptions (e.g., Saccharum officinarum, Pennisetum purpureum), the bioenergy crops exhibit broad climatic tolerance, which allows tremendous flexibility in choosing crops, especially in areas with high summer rainfall and long growing seasons (e.g., southeastern US, Amazon Basin, eastern Australia). Unsurprisingly, the invasive species of agronomic origin have very similar global climate niche profiles as the proposed bioenergy crops, also demonstrating broad climatic tolerance. The ecoregional evaluation of bioenergy crops and known invasive species demonstrates tremendous overlap at both high (EI≥30) and moderate (EI≥20) climate suitability. The southern and western US ecoregions support the greatest number of invasive species of agronomic origin, especially the Southeastern USA Plains, Mixed Woods Plains, and Mediterranean California. Many regions of the world have a suitable climate for several bioenergy crops allowing selection of agro-ecoregionally appropriate crops. This model knowingly ignores the complex biotic interactions and edaphic conditions, but provides a robust assessment of the climate

  16. A double-hurdle model estimation of cocoa farmers' willingness to pay for crop insurance in Ghana.

    PubMed

    Okoffo, Elvis Dartey; Denkyirah, Elisha Kwaku; Adu, Derick Taylor; Fosu-Mensah, Benedicta Yayra

    2016-01-01

    Agriculture is an important sector in Ghana's economy, however, with high risk due to natural factors like climate change, pests and diseases and bush fires among others. Farmers in the Brong-Ahafo region of Ghana which is known as one of the major cocoa producing regions, face these risks which sometimes results in crop failure. The need for farmers to therefore insure their farms against crop loss is crucial. Insurance has been a measure to guard against risk. The aim of this study was to assess cocoa farmers' willingness to access crop insurance, the factors affecting willingness to pay (WTP) for crop insurance scheme and insurance companies' willingness to provide crop insurance to cocoa farmers. Multi-stage sampling technique was used to sample 240 farmers from four communities in the Dormaa West District in Brong-Ahafo Region. The double-hurdle model shows that age, marital status and education significantly and positively influenced cocoa farmer's willingness to insure their farms whiles household size and cropped area negatively influenced farmers' willingness to insure their farms. Similarly, age, household size and cropped area significantly and positively influenced the premium cocoa farmers were willing to pay whiles marital status and cocoa income negatively influenced the premium farmers were willing to pay. The contingent valuation method shows that the maximum, minimum and average amounts cocoa farmers are willing to pay for crop insurance per production cost per acre was GH¢128.40, GH¢32.10 and GH¢49.32 respectively. Insurance companies do not have crop insurance policy but willing to provide crop insurance policy to cocoa farmers on a condition that farmers adopt modern cultivation practices to reduce the level of risk. The study recommends that cocoa farmers should be well educated on crop insurance and should be involved in planning the crop insurance scheme in order to conclude on the premium to be paid by them. PMID:27386322

  17. Global climate niche estimates for bioenergy crops and invasive species of agronomic origin: potential problems and opportunities.

    PubMed

    Barney, Jacob N; DiTomaso, Joseph M

    2011-03-09

    The global push towards a more biomass-based energy sector is ramping up efforts to adopt regionally appropriate high-yielding crops. As potential bioenergy crops are being moved around the world an assessment of the climatic suitability would be a prudent first step in identifying suitable areas of productivity and risk. Additionally, this assessment also provides a necessary step in evaluating the invasive potential of bioenergy crops, which present a possible negative externality to the bioeconomy. Therefore, we provide the first global climate niche assessment for the major graminaceous (9), herbaceous (3), and woody (4) bioenergy crops. Additionally, we contrast these with climate niche assessments for North American invasive species that were originally introduced for agronomic purposes as examples of well-intentioned introductions gone awry. With few exceptions (e.g., Saccharum officinarum, Pennisetum purpureum), the bioenergy crops exhibit broad climatic tolerance, which allows tremendous flexibility in choosing crops, especially in areas with high summer rainfall and long growing seasons (e.g., southeastern US, Amazon Basin, eastern Australia). Unsurprisingly, the invasive species of agronomic origin have very similar global climate niche profiles as the proposed bioenergy crops, also demonstrating broad climatic tolerance. The ecoregional evaluation of bioenergy crops and known invasive species demonstrates tremendous overlap at both high (EI≥30) and moderate (EI≥20) climate suitability. The southern and western US ecoregions support the greatest number of invasive species of agronomic origin, especially the Southeastern USA Plains, Mixed Woods Plains, and Mediterranean California. Many regions of the world have a suitable climate for several bioenergy crops allowing selection of agro-ecoregionally appropriate crops. This model knowingly ignores the complex biotic interactions and edaphic conditions, but provides a robust assessment of the climate

  18. Development of an Assimilation Scheme for the Estimation of Drought-Induced Yield Losses Based on Multi-Source Remote Sensing and the AcquaCrop Model

    NASA Astrophysics Data System (ADS)

    Silvestro, Paolo Cosmo; Casa, Raffaele; Pignatti, Stefano; Castaldi, Fabio; Yang, Hao; Yang, Guijun

    2014-11-01

    In the context of the Dragon-3 Farmland Drought project, our research deals with the development of methods for the assimilation of biophysical variables, estimated from multi-source remote sensing, into the AquaCrop model, in order to estimate the yield losses due to drought both at the farm and at the regional scale. The first part of this project was employed to refine a methodology to obtain maps of leaf area index (LAI), canopy cover (CC), fraction of adsorbed photosynthetically active radiation (FAPAR) and chlorophyll (Cab) from satellite optical data, using algorithms based on the training of artificial neural networks (ANN) on PROSAIL model simulations. In the second part, retrieved values of CC were assimilated into the AquaCrop model using the assimilation method of the Ensemble Kalman Filter to estimate grain wheat yield at the field scale.

  19. A critical analysis of three remote sensing-based actual evapotranspiration assessment methods over sparse crops agricultural areas

    NASA Astrophysics Data System (ADS)

    Cammalleri, Carmelo; Ciraolo, Giuseppe; La Loggia, Goffredo; Minacapilli, Mario

    2010-10-01

    During last two decades the increasing availability of remotely sensed acquisitions in the thermal infrared part of the spectrum has encouraged hydrologist community to develop models and methodologies based on these kind of data. The aim of this paper is to compare three methods developed to assess the actual evapotranspiration spatial distribution by means of remote sensing data. The comparison was focused on the differences between the "single" (SEBAL) and "two" source (TSEB) surface energy balance approaches and the S-SEBI semi-empirical method. The first assumes a semiempirical internal calibration for the sensible heat flux assessment; the second uses a physically based approach in order to assess separately the soil and vegetation fluxes. Finally, the last one is based on the correlation between albedo and surface temperature for evaporative fraction estimations. The models were applied using 7 high resolution images, collected by an airborne platform between June and October 2008, approximately every 3 weeks. The acquired data include multi-spectral images (red, green and near infrared) and thermal infrared images for surface temperature estimation. The study area, located in the south-west cost of Sicily, Italy), is characterised by the presence of typical Mediterranean cultivations: olive, vineyard and citrus. Due to irrigation supplies and rainfall events, the water availability for the crops varies in time and this allowed to perform the comparison in a wide range of the modelled variables. Additionally, the availability of high spatial resolution images allowed the testing of the models performances at field scale despite the high vegetation fragmentation of the study area. The comparison of models performance highlights a good agreements of model estimations, analyzed by means of MAD (Mean Absolute Differences) and MAPD (Mean Absolute Percent Differences) indices, especially in terms of study area averaged fluxes. The analysis in correspondence of

  20. Worldwide Historical Estimates of Leaf Area Index, 1932-2000

    SciTech Connect

    Scurlock, JMO

    2002-02-06

    Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 and other vegetation parameters. The LA1 data are linked to a bibliography of over 300 original source references. These historic LA1 data are mostly from natural and seminatural (managed) ecosystems, although some agricultural estimates are also included. Although methodologies for determining LA1 have changed over the decades, it is useful to represent the inconsistencies (e.g., in maximum value reported for a particular biome) that are actually found in the scientific literature. Needleleaf (coniferous) forests are by far the most commonly measured biome/land cover types in this compilation, with 22% of the measurements from temperate evergreen needleleaf forests, and boreal evergreen needleleaf forests and crops the next most common (about 9% each). About 40% of the records in the data set were published in the past 10 years (1991-2000), with a further 20% collected between 1981 and 1990. Mean LAI ({+-} standard deviation), distributed between 15 biome/land cover classes, ranged from 1.31 {+-} 0.85 for deserts to 8.72 {+-} 4.32 for tree plantations, with evergreen forests (needleleaf and broadleaf) displaying the highest LA1 among the natural terrestrial vegetation classes. We have identified statistical outliers in this data set, both globally and according to the different biome/land cover classes, but despite some decreases in mean LA1 values reported

  1. Effect of climate change in herbivorous livestock systems, including arable crops, in the French area.

    NASA Astrophysics Data System (ADS)

    Ruget, F.; J; Moreau, -C.; Ferrand, M.; Poisson, S.; Gate, P.; Lacroix, B.; Lorgeou, J.; Cloppet, E.; Souverain, F.

    2009-09-01

    The effects of atmospheric changes on climate are assessed through GCM (General circulation model). We have used the results of one of these models, the ARPEGE model, developed by the CNRM (Météo-France) concerning two scenarios of economic, technical and socio-economic development. There are the A2 scenario, with little attention to GHG emissions leading to a high CO2 concentration in the atmosphere at the end of the century (800 ppm) and the B1 scenario, a moderate scenario where the CO2 concentration would be better controlled, allowing to reach only 550 ppm at the end of the century. Our study contains studies at 2 periods in the future, the near (2020-2049) and the distant (2070-2099) future, using a mean effect for each period, without any representation of the evolution inside each period. We have done three types of analyses using the present and future climate data : first, we analyzed the climatic data, with means, maps and multiple factor analysis second, we used a crop model for grass, alfalfa and arable crops third, we analyze the evolution of some agrometeorological criteria In the climate analysis, out of the known effects (higher temperature, lower precipitation), the most interesting part for the agriculture is the spatial distribution of the changes. We showed the spatial evolution of the 10 main climates defined using the MFA of spatial data : climates of the low mountains will go up and the part of the high mountain climate will be reduced, the area of the Mediterranean climate will be larger, and the Atlantic front will be dryer. Main crop model results concern phenology and yield of crops. As phenological results, all the harvests are put forward, as well for cut crops (grass and alfalfa) as for arable crops. As adaptation, the sowing dates of the spring crops (maize) can be put forward too. The direction of the variation of yields depends on the period of the future, on the scenario and mainly on the effect of CO2 concentration. Because of

  2. Estimation of Crop Gross Primary Production (GPP). 2; Do Scaled (MODIS) Vegetation Indices Improve Performance?

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Zhang, Xiaoyang; Suyker, Andrew; Verma, Shashi; Shuai, Yanmin; Middleton, Elizabeth M.

    2015-01-01

    Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the

  3. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems

    USGS Publications Warehouse

    Glenn, E.P.; Neale, C. M. U.; Hunsaker, D.J.; Nagler, P.L.

    2011-01-01

    Crop coefficients were developed to determine crop water needs based on the evapotranspiration (ET) of a reference crop under a given set of meteorological conditions. Starting in the 1980s, crop coefficients developed through lysimeter studies or set by expert opinion began to be supplemented by remotely sensed vegetation indices (VI) that measured the actual status of the crop on a field-by-field basis. VIs measure the density of green foliage based on the reflectance of visible and near infrared (NIR) light from the canopy, and are highly correlated with plant physiological processes that depend on light absorption by a canopy such as ET and photosynthesis. Reflectance-based crop coefficients have now been developed for numerous individual crops, including corn, wheat, alfalfa, cotton, potato, sugar beet, vegetables, grapes and orchard crops. Other research has shown that VIs can be used to predict ET over fields of mixed crops, allowing them to be used to monitor ET over entire irrigation districts. VI-based crop coefficients can help reduce agricultural water use by matching irrigation rates to the actual water needs of a crop as it grows instead of to a modeled crop growing under optimal conditions. Recently, the concept has been applied to natural ecosystems at the local, regional and continental scales of measurement, using time-series satellite data from the MODIS sensors on the Terra satellite. VIs or other visible-NIR band algorithms are combined with meteorological data to predict ET in numerous biome types, from deserts, to arctic tundra, to tropical rainforests. These methods often closely match ET measured on the ground at the global FluxNet array of eddy covariance moisture and carbon flux towers. The primary advantage of VI methods for estimating ET is that transpiration is closely related to radiation absorbed by the plant canopy, which is closely related to VIs. The primary disadvantage is that they cannot capture stress effects or soil

  4. Developing in situ non-destructive estimates of crop biomass to address issues of scale in remote sensing

    USGS Publications Warehouse

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Ground-based estimates of aboveground wet (fresh) biomass (AWB) are an important input for crop growth models. In this study, we developed empirical equations of AWB for rice, maize, cotton, and alfalfa, by combining several in situ non-spectral and spectral predictors. The non-spectral predictors included: crop height (H), fraction of absorbed photosynthetically active radiation (FAPAR), leaf area index (LAI), and fraction of vegetation cover (FVC). The spectral predictors included 196 hyperspectral narrowbands (HNBs) from 350 to 2500 nm. The models for rice, maize, cotton, and alfalfa included H and HNBs in the near infrared (NIR); H, FAPAR, and HNBs in the NIR; H and HNBs in the visible and NIR; and FVC and HNBs in the visible; respectively. In each case, the non-spectral predictors were the most important, while the HNBs explained additional and statistically significant predictors, but with lower variance. The final models selected for validation yielded an R2 of 0.84, 0.59, 0.91, and 0.86 for rice, maize, cotton, and alfalfa, which when compared to models using HNBs alone from a previous study using the same spectral data, explained an additional 12%, 29%, 14%, and 6% in AWB variance. These integrated models will be used in an up-coming study to extrapolate AWB over 60 × 60 m transects to evaluate spaceborne multispectral broad bands and hyperspectral narrowbands.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Pesticide occurrence in groundwater in areas of high-density row crop production in Alabama, 2009

    USGS Publications Warehouse

    Moreland, Richard S.

    2011-01-01

    High-density row crop production occurs in three areas of Alabama that are underlain by productive aquifers, northern Alabama, southeastern Alabama, and Baldwin County in southwestern Alabama. The U.S. Geological Survey collected five groundwater samples from each of these three areas during 2009 for analysis of selected pesticides. Results of these analyses showed detections for 37 of 152 analytes. The three most frequently detected compounds were atrazine, 2-Chloro-4-isopropylamino-6-amino-triazine (CIAT), and metolachlor. The highest concentration for any analyte was 4.08 micrograms per liter for metolachlor.

  7. Evaluation of spatial filtering on the accuracy of wheat area estimate

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Delima, A. M.

    1982-01-01

    A 3 x 3 pixel spatial filter for postclassification was used for wheat classification to evaluate the effects of this procedure on the accuracy of area estimation using LANDSAT digital data obtained from a single pass. Quantitative analyses were carried out in five test sites (approx 40 sq km each) and t tests showed that filtering with threshold values significantly decreased errors of commission and omission. In area estimation filtering improved the overestimate of 4.5% to 2.7% and the root-mean-square error decreased from 126.18 ha to 107.02 ha. Extrapolating the same procedure of automatic classification using spatial filtering for postclassification to the whole study area, the accuracy in area estimate was improved from the overestimate of 10.9% to 9.7%. It is concluded that when single pass LANDSAT data is used for crop identification and area estimation the postclassification procedure using a spatial filter provides a more accurate area estimate by reducing classification errors.

  8. Can we use photography to estimate radiation interception by a crop canopy?

    PubMed

    Chakwizira, E; Meenken, E D; George, M J; Fletcher, A L

    2015-03-01

    Accuracy of determining radiation interception, and hence radiation use efficiency, depends on the method of measuring photosynthetically active radiation intercepted. Methods vary, from expensive instruments such as Sunfleck ceptometers to simple methods such as digital photography. However, before universal use of digital photography there is need to determine its reliability and compare it with conventional, but expensive, methods. In a series of experiments at Lincoln, New Zealand, canopy development for barley, wheat, white clover and four forage brassica species was determined using both digital photographs and Sunfleck ceptometer. Values obtained were used to calculate conversion coefficient (Kf/Ki) ratios between the two methods. Digital photographs were taken at 45° and 90° for barley, wheat and white clover and at only 90° for brassicas. There was an interaction of effects of crop and cultivar for the cereal crops. Barley closed canopies earlier than wheat, and 'Emir' barley and 'Stettler' wheat had consistently higher canopy cover than 'Golden Promise' and 'HY459', respectively. Canopy cover was consistently larger at 45° than 90° for cereals. However, for white clover, the angle of digital photography was not important. There was also an interaction between effects of species and method of determining canopy cover for brassicas. Photographs gave higher cover values than ceptometer for forage rape and turnip, but the relationship was variable for forage kale and swede. Kf/Ki ratios of 1.0-1.10 for cereals, white clover and forage rape and turnip show that digital photographs can be used to estimated radiation interception, in place of Sunfleck ceptometer, for these crops.

  9. Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images

    NASA Astrophysics Data System (ADS)

    Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

    2015-05-01

    As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

  10. Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

    PubMed

    Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

    2015-05-12

    As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems.

  11. Mapping paddy rice planting area in wheat-rice double-cropped areas through integration of Landsat-8 OLI, MODIS, and PALSAR images.

    PubMed

    Wang, Jie; Xiao, Xiangming; Qin, Yuanwei; Dong, Jinwei; Zhang, Geli; Kou, Weili; Jin, Cui; Zhou, Yuting; Zhang, Yao

    2015-01-01

    As farmland systems vary over space and time (season and year), accurate and updated maps of paddy rice are needed for studies of food security and environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural-urban complex (Jiangsu Province, China) and explored the potential utility of integrating time series optical images (Landsat-8, MODIS) and radar images (PALSAR) in mapping paddy rice planting areas. We first identified several main types of non-cropland land cover and then identified paddy rice fields by selecting pixels that were inundated only during paddy rice flooding periods. These key temporal windows were determined based on MODIS Land Surface Temperature and vegetation indices. The resultant paddy rice map was evaluated using regions of interest (ROIs) drawn from multiple high-resolution images, Google Earth, and in-situ cropland photos. The estimated overall accuracy and Kappa coefficient were 89.8% and 0.79, respectively. In comparison with the National Land Cover Data (China) from 2010, the resultant map better detected changes in the paddy rice fields and revealed more details about their distribution. These results demonstrate the efficacy of using images from multiple sources to generate paddy rice maps for two-crop rotation systems. PMID:25965027

  12. A scalable satellite-based crop yield mapper: Integrating satellites and crop models for field-scale estimation in India

    NASA Astrophysics Data System (ADS)

    Jain, M.; Singh, B.; Srivastava, A.; Lobell, D. B.

    2015-12-01

    Food security will be challenged over the upcoming decades due to increased food demand, natural resource degradation, and climate change. In order to identify potential solutions to increase food security in the face of these changes, tools that can rapidly and accurately assess farm productivity are needed. With this aim, we have developed generalizable methods to map crop yields at the field scale using a combination of satellite imagery and crop models, and implement this approach within Google Earth Engine. We use these methods to examine wheat yield trends in Northern India, which provides over 15% of the global wheat supply and where over 80% of farmers rely on wheat as a staple food source. In addition, we identify the extent to which farmers are shifting sow date in response to heat stress, and how well shifting sow date reduces the negative impacts of heat stress on yield. To identify local-level decision-making, we map wheat sow date and yield at a high spatial resolution (30 m) using Landsat satellite imagery from 1980 to the present. This unique dataset allows us to examine sow date decisions at the field scale over 30 years, and by relating these decisions to weather experienced over the same time period, we can identify how farmers learn and adapt cropping decisions based on weather through time.

  13. A simple method to estimate vegetation indices and crop canopy factors using field spectroscopy for solanum tuberosum during the whole phenological cycle

    NASA Astrophysics Data System (ADS)

    Perdikou, S.; Papadavid, G.; Hadjimitsis, M.; Hadjimitsis, D.; Neofytou, N.

    2013-08-01

    Field spectroscopy is a part of the remote sensing techniques and very important for studies in agriculture. A GER-1500 field spectro-radiometer was used in this study in order to retrieve the necessary spectrum data of the spring potatoes for estimating spectral vegetation indices (SVI's). A field campaign was undertaken from September to the end of November 2012 for the collection of spectro-radiometric measurements. The study area was in the Mandria Village in Paphos district in Cyprus. This paper demonstrates how crop canopy factors can be statistically related to remotely sensed data, namely vegetation indices. The paper is a part of an EU cofounded project regarding estimating crop water requirements using remote sensing techniques and informing the farmers through 3G smart telephony.

  14. Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

    PubMed Central

    Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

    2015-01-01

    It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983–1999 and 2000–2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6–11.0% and 19.5–92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming. PMID:26336098

  15. Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China.

    PubMed

    Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

    2015-01-01

    It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983-1999 and 2000-2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6-11.0% and 19.5-92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming.

  16. Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China.

    PubMed

    Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

    2015-01-01

    It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983-1999 and 2000-2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6-11.0% and 19.5-92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming. PMID:26336098

  17. Rice Crop Monitoring and Yield Estimation Through Cosmo Skymed and TerraSAR-X: A SAR-Based Experience in India

    NASA Astrophysics Data System (ADS)

    Pazhanivelan, S.; Kannan, P.; Nirmala Mary, P. Christy; Subramanian, E.; Jeyaraman, S.; Nelson, A.; Setiyono, T.; Holecz, F.; Barbieri, M.; Yadav, M.

    2015-04-01

    Rice is the most important cereal crop governing food security in Asia. Reliable and regular information on the area under rice production is the basis of policy decisions related to imports, exports and prices which directly affect food security. Recent and planned launches of SAR sensors coupled with automated processing can provide sustainable solutions to the challenges on mapping and monitoring rice systems. High resolution (3m) Synthetic Aperture Radar (SAR) imageries were used to map and monitor rice growing areas in selected three sites in TamilNadu, India to determine rice cropping extent, track rice growth and estimate yields. A simple, robust, rule-based classification for mapping rice area with multi-temporal, X-band, HH polarized SAR imagery from COSMO Skymed and TerraSAR X and site specific parameters were used. The robustness of the approach is demonstrated on a very large dataset involving 30 images across 3 footprints obtained during 2013-14. A total of 318 in-season site visits were conducted across 60 monitoring locations for rice classification and 432 field observations were made for accuracy assessment. Rice area and Start of Season (SoS) maps were generated with classification accuracies ranging from 87- 92 per cent. Using ORYZA2000, a weather driven process based crop growth simulation model; yield estimates were made with the inclusion of rice crop parameters derived from the remote sensing products viz., seasonal rice area, SoS and backscatter time series. Yield Simulation accuracy levels of 87 per cent at district level and 85- 96 per cent at block level demonstrated the suitability of remote sensing products for policy decisions ensuring food security and reducing vulnerability of farmers in India.

  18. Remote sensing of canopy dynamics and biochemical variables estimation of fodder crops

    NASA Astrophysics Data System (ADS)

    Rai, Suchit K.; Das, S. K.; Rai, A. K.

    2010-04-01

    Non-destructive monitoring and diagnosis of plant nitrogen (N) concentration status is necessary for precision in N management. Leaf -N and chlorophyll (Chl) concentration of fodder crops are important indicators of plant N status. Studies were conducted to determine the relationship between canopy hyperspectral reflectance (325 to 1075 nm) and Chl or N concentration in field grown fodder crops [bajra (Pennisetum typhoides, sorghum (Sorghum bicolor L.) in Kharif season and oat (Avena sativa) in Rabi season] without and with recommended dose of nitrogen of different crops. Nitrogen fertilizer application mainly affected leaf reflectance at 575 and 623 nm in sorghum, 565 and 657 nm in bajra and 563 and 716 nm in oat. The reflectance ratio at R581/R397 (R2=0.46**) and R619/R462 nm (R2=0.79***) had the highest correlation with sorghum and bajra leaf N concentration respectively with greatest R2 values. However in oat single reflectance at R542 (R2=0.53**) had the highest correlation with leaf N concentration. Similarly, sorghum, bajra and oat leaf Chl concentration were highly correlated with R677/R527 (R2=0.63**), R688/R409 (R2=0.71***) and R695 (R2=0.56** ), respectively. A linear relationship was found between sorghum leaf N and a simple ratio at R581/R397 (Intercept=8.85, slope=-2.64, R2=0.44). Bajra leaf N concentration was associated closely with ratio of R619/ R462, (R2= 0.78***). Oat leaf N concentration could be best estimate through single reflectance at R695 (Slope=-0.48, Intercept=0.15; R2=0.56). Similarly sorghum, bajra and oat leaf Chl could be best-estimated using reflectance ratio of R677/R527, R615/R411 and R695, respectively. Thus our results suggest that spectral reflectance measurements hold promise for the assessment of some physiological parameter at the leaf level real time monitoring of sorghum and bajra N status and N fertilizer management.

  19. Method for estimating pesticide use for county areas of the conterminous United States

    USGS Publications Warehouse

    Thelin, Gail P.; Gianessi, Leonard P.

    2000-01-01

    Information on the amount and distribution of pesticide compounds used throughout the United States is essential to evaluate the relation between water quality and pesticide use. This information is the basis of the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program studies of the effects of pesticides on water quality in 57 major hydrologic systems, or study units, located throughout the conterminous United States. To support these studies, a method was devised to estimate county pesticide use for the conterminous United States by combining (1) state-level information on pesticide use rates available from the National Center for Food and Agricultural Policy, and (2) county-level information on harvested crop acreage from the Census of Agriculture. The average annual pesticide use, the total amount of pesticides applied (in pounds), and the corresponding area treated (in acres) were compiled for the 208 pesticide compounds that are applied to crops in the conterminous United States. Pesticide use was ranked by compound and crop on the basis of the amount of each compound applied to 86 selected crops. Tabular summaries of pesticide use for NAWQA study units and for the Nation were prepared, along with maps that show the distribution of selected pesticides to agricultural land.

  20. SACRA - global data sets of satellite-derived crop calendars for agricultural simulations: an estimation of a high-resolution crop calendar using satellite-sensed NDVI

    NASA Astrophysics Data System (ADS)

    Kotsuki, S.; Tanaka, K.

    2015-01-01

    To date, many studies have performed numerical estimations of food production and agricultural water demand to understand the present and future supply-demand relationship. A crop calendar (CC) is an essential input datum to estimate food production and agricultural water demand accurately with the numerical estimations. CC defines the date or month when farmers plant and harvest in cropland. This study aims to develop a new global data set of a satellite-derived crop calendar for agricultural simulations (SACRA) and reveal advantages and disadvantages of the satellite-derived CC compared to other global products. We estimate global CC at a spatial resolution of 5 min (≈10 km) using the satellite-sensed NDVI data, which corresponds well to vegetation growth and death on the land surface. We first demonstrate that SACRA shows similar spatial pattern in planting date compared to a census-based product. Moreover, SACRA reflects a variety of CC in the same administrative unit, since it uses high-resolution satellite data. However, a disadvantage is that the mixture of several crops in a grid is not considered in SACRA. We also address that the cultivation period of SACRA clearly corresponds to the time series of NDVI. Therefore, accuracy of SACRA depends on the accuracy of NDVI used for the CC estimation. Although SACRA shows different CC from a census-based product in some regions, multiple usages of the two products are useful to take into consideration the uncertainty of the CC. An advantage of SACRA compared to the census-based products is that SACRA provides not only planting/harvesting dates but also a peak date from the time series of NDVI data.

  1. ESTIMATING PROPORTION OF AREA OCCUPIED UNDER COMPLEX SURVEY DESIGNS

    EPA Science Inventory

    Estimating proportion of sites occupied, or proportion of area occupied (PAO) is a common problem in environmental studies. Typically, field surveys do not ensure that occupancy of a site is made with perfect detection. Maximum likelihood estimation of site occupancy rates when...

  2. Using CORINE land cover and the point survey LUCAS for area estimation

    NASA Astrophysics Data System (ADS)

    Gallego, Javier; Bamps, Catharina

    2008-12-01

    CORINE land cover 2000 (CLC2000) is a European land cover map produced by photo-interpretation of Landsat ETM+ images. Its direct use for area estimation can be strongly biased and does not generally report single crops. CLC areas need to be calibrated to give acceptable statistical results. LUCAS (land use/cover area frame survey) is a point survey carried out in 2001 and 2003 in the European Union (EU15) on a systematic sample of clusters of points. LUCAS is especially useful for area estimation in geographic units that do not coincide with administrative regions, such as set of coastal areas defined with a 10 km buffer. Some variance estimation issues with systematic sampling of clusters are analysed. The contingency table obtained overlaying CLC and LUCAS gives the fine scale composition of CLC classes. Using CLC for post-stratification of LUCAS is equivalent to the direct calibration estimator when the sampling units are points. Stratification is easier to adapt to a scheme in which the sampling units are the clusters of points used in LUCAS 2001/2003.

  3. Field size, length, and width distributions based on LACIE ground truth data. [large area crop inventory experiment

    NASA Technical Reports Server (NTRS)

    Pitts, D. E.; Badhwar, G.

    1980-01-01

    The development of agricultural remote sensing systems requires knowledge of agricultural field size distributions so that the sensors, sampling frames, image interpretation schemes, registration systems, and classification systems can be properly designed. Malila et al. (1976) studied the field size distribution for wheat and all other crops in two Kansas LACIE (Large Area Crop Inventory Experiment) intensive test sites using ground observations of the crops and measurements of their field areas based on current year rectified aerial photomaps. The field area and size distributions reported in the present investigation are derived from a representative subset of a stratified random sample of LACIE sample segments. In contrast to previous work, the obtained results indicate that most field-size distributions are not log-normally distributed. The most common field size observed in this study was 10 acres for most crops studied.

  4. Characterization of crop rotations in irrigation areas of the Ebro Valley from temporal series of Landsat TM images

    NASA Astrophysics Data System (ADS)

    Martinez-Casasnovas, Jose A.; Martin-Montero, Almudena

    2004-02-01

    The present paper presents a method to characterize typical crop rotations from temporal series analysis of land use maps derived from supervised classifications of Landsat TM images. The analysis is based on spatial cross-tabulation of land use maps in raster format. As a case study, a temporal land use map series from 1993 to 2000 of the Flumen irrigation area (Huesca, Spain) was considered. The spatial cross-tabulation analysis between each pair of consecutive land use maps, performed in Idrisi 32, yielded a two dimensional matrix that allowed the identification of the typical crop rotations in the study area. Those are rice - fallow land - rice, sunflower - winter cereals - alfalfa - corn, and others as winter cereal or sunflower - fallow land - corn or alfalfa. Rice appears as a typical crop in this area, in which it is usually associated to salt- and/or sodium-affected soils. Those typical rotations have been also spatially located and represented in a map following the crop changes from one year to another year that are registered in the cross-tabulation images. The method can be useful to identify tendencies in the temporal variation of crop rotations in agricultural areas, and to locate typical areas with salt- and/or sodium-affected soils by mapping rotations in which rice is the main crop.

  5. Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Cancer.gov

    These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

  6. Remote Sensing Applications for Planning Irrigation Management. The Use of SEBAL Methodology for Estimating Crop Evapotranspiration in Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, George; Perdikou, Skevi; Hadjimitsis, Michalakis; Hadjimitsis, Diofantos

    2012-09-01

    Water allocation to crops has always been of great importance in the agricultural process. In this context, and under the current conditions, where Cyprus is facing a severe drought the last five years, the purpose of this study is basically to estimate the needed crop water requirements for supporting irrigation management and monitoring irrigation on a systematic basis for Cyprus using remote sensing techniques. The use of satellite images supported by ground measurements has provided quite accurate results. Intended purpose of this paper is to estimate the Evapotranspiration (ET) of specific crops which is the basis for irrigation scheduling and establish a procedure for monitoring and managing irrigation water over Cyprus, using remotely sensed data from Landsat TM/ ETM+ and a sound methodology used worldwide, the Surface Energy Balance Algorithm for Land (SEBAL).

  7. Calibration and algorithm development for estimation of nitrogen in wheat crop using tractor mounted N-sensor.

    PubMed

    Singh, Manjeet; Kumar, Rajneesh; Sharma, Ankit; Singh, Bhupinder; Thind, S K

    2015-01-01

    The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the N app as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. PMID:25811039

  8. Calibration and Algorithm Development for Estimation of Nitrogen in Wheat Crop Using Tractor Mounted N-Sensor

    PubMed Central

    Singh, Manjeet; Kumar, Rajneesh; Sharma, Ankit; Singh, Bhupinder; Thind, S. K.

    2015-01-01

    The experiment was planned to investigate the tractor mounted N-sensor (Make Yara International) to predict nitrogen (N) for wheat crop under different nitrogen levels. It was observed that, for tractor mounted N-sensor, spectrometers can scan about 32% of total area of crop under consideration. An algorithm was developed using a linear relationship between sensor sufficiency index (SIsensor) and SISPAD to calculate the Napp as a function of SISPAD. There was a strong correlation among sensor attributes (sensor value, sensor biomass, and sensor NDVI) and different N-levels. It was concluded that tillering stage is most prominent stage to predict crop yield as compared to the other stages by using sensor attributes. The algorithms developed for tillering and booting stages are useful for the prediction of N-application rates for wheat crop. N-application rates predicted by algorithm developed and sensor value were almost the same for plots with different levels of N applied. PMID:25811039

  9. Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data

    NASA Astrophysics Data System (ADS)

    Dong, Taifeng; Liu, Jiangui; Qian, Budong; Zhao, Ting; Jing, Qi; Geng, Xiaoyuan; Wang, Jinfei; Huffman, Ted; Shang, Jiali

    2016-07-01

    A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAIL) alone (R2 = 0.77 and RMSE = 231 g m-2). Assimilation of GLAI derived from the fusion dataset (GLAIF) resulted in a R2 of 0.71 and RMSE of 193 g m-2 while assimilating the combination of GLAIL and GLAIF led to further improvements (R2 = 0.76 and RMSE = 176 g m-2). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution

  10. Scaling up stomatal conductance from leaf to canopy using a dual-leaf model for estimating crop evapotranspiration.

    PubMed

    Ding, Risheng; Kang, Shaozhong; Du, Taisheng; Hao, Xinmei; Zhang, Yanqun

    2014-01-01

    The dual-source Shuttleworth-Wallace model has been widely used to estimate and partition crop evapotranspiration (λET). Canopy stomatal conductance (Gsc), an essential parameter of the model, is often calculated by scaling up leaf stomatal conductance, considering the canopy as one single leaf in a so-called "big-leaf" model. However, Gsc can be overestimated or underestimated depending on leaf area index level in the big-leaf model, due to a non-linear stomatal response to light. A dual-leaf model, scaling up Gsc from leaf to canopy, was developed in this study. The non-linear stomata-light relationship was incorporated by dividing the canopy into sunlit and shaded fractions and calculating each fraction separately according to absorbed irradiances. The model includes: (1) the absorbed irradiance, determined by separately integrating the sunlit and shaded leaves with consideration of both beam and diffuse radiation; (2) leaf area for the sunlit and shaded fractions; and (3) a leaf conductance model that accounts for the response of stomata to PAR, vapor pressure deficit and available soil water. In contrast to the significant errors of Gsc in the big-leaf model, the predicted Gsc using the dual-leaf model had a high degree of data-model agreement; the slope of the linear regression between daytime predictions and measurements was 1.01 (R2 = 0.98), with RMSE of 0.6120 mm s-1 for four clear-sky days in different growth stages. The estimates of half-hourly λET using the dual-source dual-leaf model (DSDL) agreed well with measurements and the error was within 5% during two growing seasons of maize with differing hydrometeorological and management strategies. Moreover, the estimates of soil evaporation using the DSDL model closely matched actual measurements. Our results indicate that the DSDL model can produce more accurate estimation of Gsc and λET, compared to the big-leaf model, and thus is an effective alternative approach for estimating and partitioning

  11. Scaling up stomatal conductance from leaf to canopy using a dual-leaf model for estimating crop evapotranspiration.

    PubMed

    Ding, Risheng; Kang, Shaozhong; Du, Taisheng; Hao, Xinmei; Zhang, Yanqun

    2014-01-01

    The dual-source Shuttleworth-Wallace model has been widely used to estimate and partition crop evapotranspiration (λET). Canopy stomatal conductance (Gsc), an essential parameter of the model, is often calculated by scaling up leaf stomatal conductance, considering the canopy as one single leaf in a so-called "big-leaf" model. However, Gsc can be overestimated or underestimated depending on leaf area index level in the big-leaf model, due to a non-linear stomatal response to light. A dual-leaf model, scaling up Gsc from leaf to canopy, was developed in this study. The non-linear stomata-light relationship was incorporated by dividing the canopy into sunlit and shaded fractions and calculating each fraction separately according to absorbed irradiances. The model includes: (1) the absorbed irradiance, determined by separately integrating the sunlit and shaded leaves with consideration of both beam and diffuse radiation; (2) leaf area for the sunlit and shaded fractions; and (3) a leaf conductance model that accounts for the response of stomata to PAR, vapor pressure deficit and available soil water. In contrast to the significant errors of Gsc in the big-leaf model, the predicted Gsc using the dual-leaf model had a high degree of data-model agreement; the slope of the linear regression between daytime predictions and measurements was 1.01 (R2 = 0.98), with RMSE of 0.6120 mm s-1 for four clear-sky days in different growth stages. The estimates of half-hourly λET using the dual-source dual-leaf model (DSDL) agreed well with measurements and the error was within 5% during two growing seasons of maize with differing hydrometeorological and management strategies. Moreover, the estimates of soil evaporation using the DSDL model closely matched actual measurements. Our results indicate that the DSDL model can produce more accurate estimation of Gsc and λET, compared to the big-leaf model, and thus is an effective alternative approach for estimating and partitioning λET.

  12. Scaling Up Stomatal Conductance from Leaf to Canopy Using a Dual-Leaf Model for Estimating Crop Evapotranspiration

    PubMed Central

    Ding, Risheng; Kang, Shaozhong; Du, Taisheng; Hao, Xinmei; Zhang, Yanqun

    2014-01-01

    The dual-source Shuttleworth-Wallace model has been widely used to estimate and partition crop evapotranspiration (λET). Canopy stomatal conductance (Gsc), an essential parameter of the model, is often calculated by scaling up leaf stomatal conductance, considering the canopy as one single leaf in a so-called “big-leaf” model. However, Gsc can be overestimated or underestimated depending on leaf area index level in the big-leaf model, due to a non-linear stomatal response to light. A dual-leaf model, scaling up Gsc from leaf to canopy, was developed in this study. The non-linear stomata-light relationship was incorporated by dividing the canopy into sunlit and shaded fractions and calculating each fraction separately according to absorbed irradiances. The model includes: (1) the absorbed irradiance, determined by separately integrating the sunlit and shaded leaves with consideration of both beam and diffuse radiation; (2) leaf area for the sunlit and shaded fractions; and (3) a leaf conductance model that accounts for the response of stomata to PAR, vapor pressure deficit and available soil water. In contrast to the significant errors of Gsc in the big-leaf model, the predicted Gsc using the dual-leaf model had a high degree of data-model agreement; the slope of the linear regression between daytime predictions and measurements was 1.01 (R2 = 0.98), with RMSE of 0.6120 mm s−1 for four clear-sky days in different growth stages. The estimates of half-hourly λET using the dual-source dual-leaf model (DSDL) agreed well with measurements and the error was within 5% during two growing seasons of maize with differing hydrometeorological and management strategies. Moreover, the estimates of soil evaporation using the DSDL model closely matched actual measurements. Our results indicate that the DSDL model can produce more accurate estimation of Gsc and λET, compared to the big-leaf model, and thus is an effective alternative approach for estimating and

  13. The large area crop inventory experiment: An experiment to demonstrate how space-age technology can contribute to solving critical problems here on earth

    NASA Technical Reports Server (NTRS)

    1977-01-01

    The large area crop inventory experiment is being developed to predict crop production through satellite photographs. This experiment demonstrates how space age technology can contribute to solving practical problems of agriculture management.

  14. LARGE AREA MONITORING FOR PESTICIDAL TRANSGENIC CROPS: HOW SPECTRAL IMAGING MAY PLAY A ROLE

    EPA Science Inventory

    Crops genetically engineered to contain a bacterial gene that expresses an insecticidal protein from Bacillus thuringiensis are regulated by EPA under the Federal Insecticide Fungicide and Rodenticide Act (FIFRA). EPA has declared crops containing transgenic pesticidal traits to...

  15. Separation of agroclimatic areas for optimal crop growing within the framework of the natural-agricultural zoning of Russia

    NASA Astrophysics Data System (ADS)

    Bulgakov, D. S.; Rukhovich, D. I.; Shishkonakova, E. A.; Vil'chevskaya, E. V.

    2016-09-01

    The separation of agroclimatic areas for optimal crop growing within is suggested within the framework of the natural-agricultural zoning of Russia developed under the supervision of I. Karmanov. Overall, 64 agroclimatic areas have been separated in Russia. They are specified by the particular soil and agroclimatic conditions and by the particular crops recommended for cultivation. The biological potential of these crops should correspond to the soil potential of the given area. A combined scheme of the natural-agricultural zoning of Russia and the separated agroclimatic areas is presented. It is argued that the information contained in this scheme can be used for developing landscape-adaptive farming systems, land cadaster, and land valuation; it is also helpful for terrain and remote sensing monitoring of soil fertility on arable lands and for soilecological monitoring.

  16. Impacts of Different Assimilation Methodologies on Crop Yield Estimates Using Active and Passive Microwave Dataset at L-Band

    NASA Astrophysics Data System (ADS)

    Liu, P.; Bongiovanni, T. E.; Monsivais-Huertero, A.; Bindlish, R.; Judge, J.

    2013-12-01

    Accurate estimates of crop yield are important for managing agricultural production and food security. Although the crop growth models, such as the Decision Support System Agrotechnology Transfer (DSSAT), have been used to simulate crop growth and development, the crop yield estimates still diverge from the reality due to different sources of errors in the models and computation. Auxiliary observations may be incorporated into such dynamic models to improve predictions using data assimilation. Active and passive (AP) microwave observations at L-band (1-2 GHz) are sensitive to dielectric and geometric properties of soil and vegetation, including soil moisture (SM), vegetation water content (VWC), surface roughness, and vegetation structure. Because SM and VWC are one of the governing factors in estimating crop yield, microwave observations may be used to improve crop yield estimates. Current studies have shown that active observations are more sensitive to the surface roughness of soil and vegetation structure during the growing season, while the passive observations are more sensitive to the SM. Backscatter and emission models linked with the DSSAT model (DSSAT-A-P) allow assimilation of microwave observations of backscattering coefficient (σ0) and brightness temperature (TB) may provide biophysically realistic estimates of model states and parameters. The present ESA Soil Moisture Ocean Salinity (SMOS) mission provides passive observations at 1.41 GHz at 25 km every 2-3 days, and the NASA/CNDAE Aquarius mission provides L-band AP observations at spatial resolution of 150 km with a repeat coverage of 7 days for global SM products. In 2014, the planned NASA Soil Moisture Active Passive mission will provide AP observations at 1.26 and 1.41 GHz at the spatial resolutions of 3 and 30 km, respectively, with a repeat coverage of 2-3 days. The goal of this study is to understand the impacts of assimilation of asynchronous and synchronous AP observations on crop yield

  17. Large Area Crop Inventory Experiment (LACIE). Results of LACIE integrated drought analysis (Southern U.S. Great Plains drought 1975-76)

    NASA Technical Reports Server (NTRS)

    Thompson, D. R.

    1976-01-01

    The development and intensification of the drought in the United States southern Great Plains was monitored during the initial growing period of the 1975-76 winter wheat crop. Because of the severity of the drought conditions, a drought analysis plan was developed and implemented beginning on March 8, 1976. Sample segments and full-frame imagery were used at 9-day intervals to identify the drought area and quantify the effects on the wheat acreage. Yield model simulations were run to extrapolate the effects of the drought on yield estimates at harvest, assuming 10 and 90 percent of normal rainfall for subsequent months and 30-day forecast. A survey of LANDSAT data for improvement of distribution of rainfall patterns in the drought area was done for April and yield models run for drought affected crop reporting districts. Special aggregations were performed by the Crop Assessment Subsystem on the drought area to evaluate the utility of remote sensing to monitor the effect of the drought on wheat area, yield, and production.

  18. Evaluation of thermal remote sensing indices to estimate crop evapotranspiration coefficients

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Remotely sensed data such as spectral reflectance and infrared canopy temperature can be used to quantify crop canopy cover and/or crop water stress, often through the use of vegetation indices calculated from the near-infrared and red bands, and stress indices calculated from the thermal wavelength...

  19. LACIE large area acreage estimation. [United States of America

    NASA Technical Reports Server (NTRS)

    Chhikara, R. S.; Feiveson, A. H. (Principal Investigator)

    1979-01-01

    A sample wheat acreage for a large area is obtained by multiplying its small grains acreage estimate as computed by the classification and mensuration subsystem by the best available ratio of wheat to small grains acreages obtained from historical data. In the United States, as in other countries with detailed historical data, an additional level of aggregation was required because sample allocation was made at the substratum level. The essential features of the estimation procedure for LACIE countries are included along with procedures for estimating wheat acreage in the United States.

  20. Retrieving Crops Green Area Index from High Temporal and Spatial Resolution Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Veloso, A.; Demarez, V.; Ceschia, E.

    2012-04-01

    This paper aims at firstly evaluating the correspondence between Normalized Difference Vegetation Index (NDVI) products from Formosat-2 (F2) and SPOT sensors and then to perform a comparative analysis of two methods for retrieving Green Area Index from high spatial and temporal resolution satellite data (F2 and SPOT). For this purpose, an empirical approach using NDVI plus field data and a Neural Network approach using the PROSAIL model are compared over four different crops: maize, soybean, sunflower and wheat. The performance of both methods were evaluated and compared with in-situ direct (destructive) and indirect (hemispherical photos) measurements. Results suggest better performances for the empirical approach (R², RMSE). Still the physically-based method leads to good results (R², RMSE). The latter seems to be more promising due to its portability and independence from field measurements. Therefore new perspectives to improve this approach are being envisaged.

  1. Results of Large Area Crop Inventory Experiment (LACIE) drought analysis (South Dakota drought 1976)

    NASA Technical Reports Server (NTRS)

    Thompson, D. R.

    1976-01-01

    LACIE using techniques developed from the southern Great Plains drought analysis indicated the potential for drought damage in South Dakota. This potential was monitored and as it became apparent that a drought was developing, LACIE implemented some of the procedures used in the southern Great Plains drought. The technical approach used in South Dakota involved the normal use of LACIE sample segments (5 x 6 nm) every 18 days. Full frame color transparencies (100 x 100 nm) were used on 9 day intervals to identify the drought area and to track overtime. The green index number (GIN) developed using the Kauth transformation was computed for all South Dakota segments and selected North Dakota segments. A scheme for classifying segments as drought affected or not affected was devised and tested on all available 1976 South Dakota data. Yield model simulations were run for all CRD's Crop Reporting District) in South Dakota.

  2. Generalized flood-frequency estimates for urban areas in Missouri

    USGS Publications Warehouse

    Gann, Ector Eugene

    1971-01-01

    A method is presented for estimating flood-frequency information for urban areas in Missouri. Flood-frequency relations are presented which provide an estimate of the flood-peak discharge for floods with recurrence intervals from 2.33 to 100 years for basins with various degrees of existing or projected urban development. Drainage area sizes for which the relations are applicable range from 0.1 to 50 square miles. These generalized relations will be useful to the urban planner and designer until more comprehensive studies are completed for the individual urban areas within the State. The relations will also be of use in the definition of flood-hazard areas in Missouri.

  3. Classifying cropping area of middle Heihe River Basin in China using multitemporal Normalized Difference Vegetation Index data

    NASA Astrophysics Data System (ADS)

    Han, Huibang; Ma, Mingguo; Wang, Xufeng; Ma, Shoucun

    2014-01-01

    Accurate information regarding the structure of crops is critical for the improvement and optimization of land surface models. Multitemporal remote sensing imagery is more effective to determine the crop structure than the single-temporal images because they contain phenological information. Crop structure was extracted based on time series of moderate-resolution imaging spectroradiometer (MODIS) data in the middle Heihe River Basin. A time series of Normalized Difference Vegetation Index (NDVI) data with a 3-day temporal resolution was composed based on daily MODIS reflectance products (MOD 09) from January to December 2011. A total of 120 scenes of composited imagery were integrated into an image data cube of NDVI time series, which was used to extract crop structure for the study area. The spectral curves of corn, wheat, rape, vegetables, and other crops are based on both in situ measurements and visual interpretation. The major crop types were classified by using the adaptive boosting (Adaboost) and support vector machine (SVM) algorithms. The results show that the classification accuracy of Adaboost and SVM was 86.01% and 70.28%, respectively, with Kappa coefficients of 0.8351 and 0.6438, respectively. Summarizing the classification methods used in this study effectively characterize the spatial distribution of the main crops.

  4. Estimating crop canopy coverage of cotton plants within the FOV of an infrared thermometer using a two band photodiode sensor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The majority of irrigated area in the Southern High Plains region of Texas is by center pivot systems; all are drawing water from the Ogallala Aquifer. Automating the center pivot system to schedule irrigations automatically based on crop canopy temperature measured with infrared thermometers (IRT)...

  5. A Unified Experimental Approach for Estimation of Irrigationwater and Nitrate Leaching in Tree Crops

    NASA Astrophysics Data System (ADS)

    Hopmans, J. W.; Kandelous, M. M.; Moradi, A. B.

    2014-12-01

    Groundwater quality is specifically vulnerable in irrigated agricultural lands in California and many other(semi-)arid regions of the world. The routine application of nitrogen fertilizers with irrigation water in California is likely responsible for the high nitrate concentrations in groundwater, underlying much of its main agricultural areas. To optimize irrigation/fertigation practices, it is essential that irrigation and fertilizers are applied at the optimal concentration, place, and time to ensure maximum root uptake and minimize leaching losses to the groundwater. The applied irrigation water and dissolved fertilizer, as well as root growth and associated nitrate and water uptake, interact with soil properties and fertilizer source(s) in a complex manner that cannot easily be resolved. It is therefore that coupled experimental-modeling studies are required to allow for unraveling of the relevant complexities that result from typical field-wide spatial variations of soil texture and layering across farmer-managed fields. We present experimental approaches across a network of tree crop orchards in the San Joaquin Valley, that provide the necessary soil data of soil moisture, water potential and nitrate concentration to evaluate and optimize irrigation water management practices. Specifically, deep tensiometers were used to monitor in-situ continuous soil water potential gradients, for the purpose to compute leaching fluxes of water and nitrate at both the individual tree and field scale.

  6. Vaccination coverage in India: a small area estimation approach.

    PubMed

    Pramanik, Santanu; Muthusamy, Nithiyananthan; Gera, Rajeev; Laxminarayan, Ramanan

    2015-03-30

    Information on population health indicators in India come from a number of surveys that vary in periodicity, scope and detail. In the case of immunization, the most recent coverage indicators are derived from the first round of Annual Health Survey (AHS-1, 2010-11), but these were conducted only in 9 of 35 states and union territories. The most recent national surveys of immunization coverage were conducted in 2009 (Coverage Evaluation Survey) by UNICEF. Therefore, reliable immunization coverage data for the entire country since 2009 is lacking. We used an established approach of small area estimation to predict coverage rates of several vaccinations for the remaining 26 states (not covered by AHS-1) in 2011. In our method, we considered a linear mixed model that combines data from five cross sectional surveys representing five different time points. Our model encompasses sampling error of the survey estimates, area specific random effects, autocorrelated area by time random effects and hence, borrows strength across areas and time points both. Model-based estimates for 2011 are almost identical to the AHS-1 estimates for the nine states, suggesting that our model provides reliable prediction of vaccination coverage as AHS-1 estimates are highly precise because of their large sample size. Results indicate that coverage inequality between rural and urban areas has been reduced significantly for most states in India. The National Rural Health Mission has had both supply side and demand side effects on the immunization programme in rural India. In combination, these effects may have contributed to the reduction of vaccination coverage gaps between urban and rural areas.

  7. Estimating 3-dimensional colony surface area of field corals

    EPA Science Inventory

    Colony surface area is a critical descriptor for biological and physical attributes of reef-building (scleractinian, stony) corals. The three-dimensional (3D) size and structure of corals are directly related to many ecosystem values and functions. Most methods to estimate colony...

  8. Space Data for Crop Management

    NASA Technical Reports Server (NTRS)

    1990-01-01

    CROPIX, Inc., formed in 1984 by Frank Lamb, president of the Eastern Oregon Farming Company, monitors primarily potato crops in a 20,000 square mile area of northern Oregon and central Washington. Potatoes are a high value specialty crop that can be more profitable to the farmer if he has advance knowledge of market conditions, knows when to harvest, and when to take it to market. By processing and collecting data collected by the NASA-developed Landsat Earth Resources survey satellites, Lamb is able to provide accurate information on crop acreage and conditions on a more timely basis than the routine estimates by the USDA. CROPIX uses Landsat data to make acreage estimates of crops, and to calculate a field-by-field vegetative index number. CROPIX then distributes to its customers a booklet containing color-coded maps, an inventory of crops, plus data and graphs on crop conditions and other valuable information.

  9. European-Scale Evaluation Of The Capacity Of Remote Sensing Indicators To Estimate Regional Crop Yields

    NASA Astrophysics Data System (ADS)

    Lopez-Lozano, Raul; Duveiller, Gregory; Seguini, Lorenzo; Garcia-Condado, Sara; Baruth, Bettina

    2013-12-01

    This study presents a systematic evaluation of how remote sensing indicators relate to official crop yield time series for wheat, barley and maize over Europe at the regional level. These indicators consist of cumulated values of 1-km fAPAR products from SPOT- VEGETATION that are currently being operationally used in the MARS Crop Yield Forecasting System (MCYFS) and which are compatible with future services that will be provided by the European Copernicus Programme. The study demonstrates how regional fAPAR time series are able to provide valuable information for many regions about crop yield potentials during the growing season.

  10. Estimating global specific leaf area from MODIS leaf area index and model-simulated foliage mass

    NASA Astrophysics Data System (ADS)

    Baruah, P. J.; Yasuoka, Y.; Ito, A.; Dye, D.

    2006-12-01

    Specific leaf area (SLA) is an important leaf trait that is universally correlated positively to leaf nitrogen, leaf turnover rates, relative growth rate and most importantly, photosynthetic capacity. Though SLA is genetically encoded, it is often spatially variable within a species and within a single biome due to variable environmental conditions. However, without a global SLA map, global ecosystem models that use SLA, generally fix a single value for a particular biome. In this study, we develop a methodology to estimate global SLA from a remote sensing-derived key ecosystem variable, leaf area index and foliage mass estimated by a terrestrial ecosystem model SimCYCLE. SimCYCLE uses climatic inputs, land-cover data and biomass-allocation to estimate leaf biomass in a process-based scheme. Model-estimated foliage mass and MODIS leaf area index are assumed to represent the most-accurate ground condition to estimate SLA for the entire globe at 0.5 degree resolution. Validation of estimated specific leaf area is done with a published field-sampled global dataset, and additional field-sampled SLA data collected from published literatures. The validation data is also used for rectification of unrealistic values of estimated SLA to produce a global SLA map, which we strongly believe, would be valuable to improve estimates of carbon dynamic across individual biomes upon assimilation with the ecosystem models.

  11. Estimation of yield and water requirements of maize crops combining high spatial and temporal resolution images with a simple crop model, in the perspective of the Sentinel-2 mission

    NASA Astrophysics Data System (ADS)

    Battude, Marjorie; Bitar, Ahmad Al; Brut, Aurore; Cros, Jérôme; Dejoux, Jean-François; Huc, Mireille; Marais Sicre, Claire; Tallec, Tiphaine; Demarez, Valérie

    2016-04-01

    Water resources are under increasing pressure as a result of global change and of a raising competition among the different users (agriculture, industry, urban). It is therefore important to develop tools able to estimate accurately crop water requirements in order to optimize irrigation while maintaining acceptable production. In this context, remote sensing is a valuable tool to monitor vegetation development and water demand. This work aims at developing a robust and generic methodology mainly based on high resolution remote sensing data to provide accurate estimates of maize yield and water needs at the watershed scale. Evapotranspiration (ETR) and dry aboveground biomass (DAM) of maize crops were modeled using time series of GAI images used to drive a simple agro-meteorological crop model (SAFYE, Duchemin et al., 2005). This model is based on a leaf partitioning function (Maas, 1993) for the simulation of crop biomass and on the FAO-56 methodology for the ETR simulation. The model also contains a module to simulate irrigation. This study takes advantage of the SPOT4 and SPOT5 Take5 experiments initiated by CNES (http://www.cesbio.ups-tlse.fr/multitemp/). They provide optical images over the watershed from February to May 2013 and from April to August 2015 respectively, with a temporal and spatial resolution similar to future images from the Sentinel-2 and VENμS missions. This dataset was completed with LandSat8 and Deimos1 images in order to cover the whole growing season while reducing the gaps in remote sensing time series. Radiometric, geometric and atmospheric corrections were achieved by the THEIA land data center, and the KALIDEOS processing chain. The temporal dynamics of the green area index (GAI) plays a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Consistent seasonal dynamics of the remotely sensed GAI was estimated by applying a radiative transfer model based on artificial neural networks (BVNET, Baret

  12. Advancements in Estimating Crop Growth Stages Using RADARSAT-2 and Terrasar-X Polarimetric Data

    NASA Astrophysics Data System (ADS)

    Lampropoulos, G.; Li, Y.; Liu, T.

    2015-04-01

    This paper uses RADARSAT-2 quad Polarimetric Synthetic Aperture Radar (PolSAR) and TerraSAR-X dual polarimetric SAR data to monitor agriculture crop growth stages. Two RADARSAT-2 Fine Quad Wide (FQW) beam modes FQ2W and FQ10W, each with 5 sets of data and 13 sets of Stripmap TerraSAR-X data were used in the study. Both RADARSAT-2 POLSAR data and TerraSARX data were acquired in summer 2012 outside Winnipeg, Manitoba, Canada. The study was carried out to two crop types: canola and wheat, each contains 5 regions of interest from ground truth crop classification map in the image scene. Polarimetric features such as differential reflectivity bands ratio, entropy, anisotropy, alpha angle, lambda, scattering diversity and polarization index were evaluated for two crop types. The results from both RADARSAT-2 and TerraSAR-X data were compared and they demonstrated clear relationships between crop growth stages and polarimetric parameters. It is observed that entropy, lambda and differential reflectivity from both data have similar responses to crop growth stages in their common coverage period. The results were also validated using ground truth information.

  13. F-Area Type IV Tank Liner Life Estimation

    SciTech Connect

    Wiersman, B. J.

    2005-10-01

    The Savannah River Site (SRS) is proceeding with closure of the Type IV waste tanks that are located in F-area. These tanks are underground concrete vaults and have been in service since the early 1960's. The interior of the concrete vault is lined with carbon steel plate. The time necessary for the carbon steel plate to disintegrate was estimated. These calculations assumed that the concrete structure was degraded and therefore the exterior of the liner is exposed to the soil conditions. Two corrosion mechanisms were examined: pitting and general corrosion. Data from soil corrosion studies performed by the National Bureau of Standards (NBS) was utilized to estimate the corrosion rate of the carbon steel liner. The following conclusions were made: (1) Cecil Clay Loam in Atlanta, Georgia, a soil tested by the NBS, is representative of the SRS soil conditions near the F-Area Type IV tanks. (2) The time to tank wall disintegration due to general corrosion only was estimated to be 770 years after concrete vault failure. (3) The time to tank wall disintegration due to pitting corrosion was estimated to be 675 years after concrete vault failure. (4) The lower bound estimate for the time to tank wall disintegration is 675 years.

  14. Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Cancer.gov

    This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

  15. Estimating the Effects of the Terminal Area Productivity Program

    NASA Technical Reports Server (NTRS)

    Lee, David A.; Kostiuk, Peter F.; Hemm, Robert V., Jr.; Wingrove, Earl R., III; Shapiro, Gerald

    1997-01-01

    The report describes methods and results of an analysis of the technical and economic benefits of the systems to be developed in the NASA Terminal Area Productivity (TAP) program. A runway capacity model using parameters that reflect the potential impact of the TAP technologies is described. The runway capacity model feeds airport specific models which are also described. The capacity estimates are used with a queuing model to calculate aircraft delays, and TAP benefits are determined by calculating the savings due to reduced delays. The report includes benefit estimates for Boston Logan and Detroit Wayne County airports. An appendix includes a description and listing of the runway capacity model.

  16. Using high resolution CIR imagery in the classification of non-cropped areas in agricultural landscapes in the UK

    NASA Astrophysics Data System (ADS)

    O'Connell, Jerome; Bradter, Ute; Benton, Tim G.

    2013-10-01

    With global food demand on course to double in the next 50 years the pressures of agricultural intensification on ecosystem services in highly managed landscapes are increasing. Within an agricultural landscape non-cropped areas are a key component of ecological heterogeneity and the sustainability of ecosystem services. Management of the landscape for both production of food and ecosystem services requires configuring the non-cropped areas in an optimal way, which, in turn requires large scale information on the distribution of non-cropped areas. In this study the Canny edge detection algorithm was used to delineate 93% of all boundaries within 422 ha of agricultural land in south east England. The resulting image was used in conjunction with vegetation indices derived from Color Infra Red (CIR) aerial photography and auxiliary landuse data in an Object Orientated (OO) Knowledge Based Classifier (KBC) to identify non-cropped areas. An overall accuracy of 94.27% (Kappa 0.91) for the KBC compared favorably with 63.04% (Kappa 0.55) for a pixel based hybrid classifier of the same area.

  17. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000

    NASA Astrophysics Data System (ADS)

    Monfreda, Chad; Ramankutty, Navin; Foley, Jonathan A.

    2008-03-01

    Croplands cover ~15 million km2 of the planet and provide the bulk of the food and fiber essential to human well-being. Most global land cover data sets from satellites group croplands into just a few categories, thereby excluding information that is critical for answering key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information about agricultural land use practices like crop selection, yield, and fertilizer use is even more limited. Here we present land use data sets created by combining national, state, and county level census statistics with a recently updated global data set of croplands on a 5 min by 5 min (~10 km by 10 km) latitude-longitude grid. The resulting land use data sets depict circa the year 2000 the area (harvested) and yield of 175 distinct crops of the world. We aggregate these individual crop maps to produce novel maps of 11 major crop groups, crop net primary production, and four physiologically based crop types: annuals/perennials, herbaceous/shrubs/trees, C3/C4, and leguminous/nonleguminous.

  18. LIFE CLIMATREE project: A novel approach for accounting and monitoring carbon sequestration of tree crops and their potential as carbon sink areas

    NASA Astrophysics Data System (ADS)

    Stergiou, John; Tagaris, Efthimios; -Eleni Sotiropoulou, Rafaella

    2016-04-01

    Climate Change Mitigation is one of the most important objectives of the Kyoto Convention, and is mostly oriented towards reducing GHG emissions. However, carbon sink is retained only in the calculation of the forests capacity since agricultural land and farmers practices for securing carbon stored in soils have not been recognized in GHG accounting, possibly resulting in incorrect estimations of the carbon dioxide balance in the atmosphere. The agricultural sector, which is a key sector in the EU, presents a consistent strategic framework since 1954, in the form of Common Agricultural Policy (CAP). In its latest reform of 2013 (reg. (EU) 1305/13) CAP recognized the significance of Agriculture as a key player in Climate Change policy. In order to fill this gap the "LIFE ClimaTree" project has recently founded by the European Commission aiming to provide a novel method for including tree crop cultivations in the LULUCF's accounting rules for GHG emissions and removal. In the framework of "LIFE ClimaTree" project estimation of carbon sink within EU through the inclusion of the calculated tree crop capacity will be assessed for both current and future climatic conditions by 2050s using the GISS-WRF modeling system in a very fine scale (i.e., 9km x 9km) using RCP8.5 and RCP4.5 climate scenarios. Acknowledgement: LIFE CLIMATREE project "A novel approach for accounting and monitoring carbon sequestration of tree crops and their potential as carbon sink areas" (LIFE14 CCM/GR/000635).

  19. Using a basin-scale hydrological model to estimate crop transpiration and soil evaporation

    NASA Astrophysics Data System (ADS)

    Kite, G.

    2000-03-01

    Increasing populations and expectations, declining crop yields and the resulting increased competition for water necesitate improvements in irrigation management and productivity. A key factor in defining agricultural productivity is to be able to simulate soil evaporation and crop transpiration. In agribusiness terms, crop transpiration is a useful process while soil and open-water evaporations are wasteful processes. In this study a distributed hydrological model was used to compute daily evaporation and transpiration for a variety of crops and other land covers within the 17,200 km 2 Gediz Basin in western Turkey. The model, SLURP, describes the complete hydrological cycle for each land cover within a series of sub-basins including all dams, reservoirs, regulators and irrigation schemes in the basin. The sub-basins and land covers are defined by analysing a digital elevation model and NOAA AVHRR satellite data. In this study, the model uses the FAO implementation of the Penman-Monteith equation to simulate soil evaporation and crop transpiration. The results of the model runs provide time series of data on streamflow at many points along the river system, abstractions and return flows from crops within the irrigation schemes and areally distributed soil evaporation and crop transpiration across the entire basin on each day of an 11 year period. The results show that evaporation and transpiration vary widely across the basin on any one day and over the irrigation season and can be used to evaluate the effectiveness of the various irrigation strategies used in the basin. The advantages of using such a model as compared to deriving evapotranspiration from satellite data are that the model obtains results for each day of an indefinitely long period, as opposed to occasional snapshots, and can also be used to simulate alternate scenarios.

  20. [Winter wheat area estimation with MODIS-NDVI time series based on parcel].

    PubMed

    Li, Le; Zhang, Jin-shui; Zhu, Wen-quan; Hu, Tan-gao; Hou, Dong

    2011-05-01

    Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

  1. Estimation of Carbon Budgets for Croplands by Combining High Resolution Remote Sensing Data with a Crop Model and Validation Ground Data

    NASA Astrophysics Data System (ADS)

    Mangiarotti, S.; Veloso, A.; Ceschia, E.; Tallec, T.; Dejoux, J. F.

    2015-12-01

    Croplands occupy large areas of Earth's land surface playing a key role in the terrestrial carbon cycle. Hence, it is essential to quantify and analyze the carbon fluxes from those agro-ecosystems, since they contribute to climate change and are impacted by the environmental conditions. In this study we propose a regional modeling approach that combines high spatial and temporal resolutions (HSTR) optical remote sensing data with a crop model and a large set of in-situ measurements for model calibration and validation. The study area is located in southwest France and the model that we evaluate, called SAFY-CO2, is a semi-empirical one based on the Monteith's light-use efficiency theory and adapted for simulating the components of the net ecosystem CO2 fluxes (NEE) and of the annual net ecosystem carbon budgets (NECB) at a daily time step. The approach is based on the assimilation of satellite-derived green area index (GAI) maps for calibrating a number of the SAFY-CO2 parameters linked to crop phenology. HSTR data from the Formosat-2 and SPOT satellites were used to produce the GAI maps. The experimental data set includes eddy covariance measurements of net CO2 fluxes from two experimental sites and partitioned into gross primary production (GPP) and ecosystem respiration (Reco). It also includes measurements of GAI, biomass and yield between 2005 and 2011, focusing on the winter wheat crop. The results showed that the SAFY-CO2 model correctly reproduced the biomass production, its dynamic and the yield (relative errors about 24%) in contrasted climatic, environmental and management conditions. The net CO2 flux components estimated with the model were overall in agreement with the ground data, presenting good correlations (R² about 0.93 for GPP, 0.77 for Reco and 0.86 for NEE). The evaluation of the modelled NECB for the different site-years highlighted the importance of having accurate estimates of each component of the NECB. Future works aim at considering

  2. A Hybrid Surface Energy Balance Approach for Large Scale Evapotranspiration Estimation and Prediction in Agricultural Areas

    NASA Astrophysics Data System (ADS)

    Neale, C. M.; Vinukollu, R. K.; Chavez, J. L.

    2005-05-01

    Over the last few years, several surface energy balance methods for the estimation of latent heat fluxes from remotely sensed satellite imagery have been introduced and/or refined. These models have shown the ability of obtaining seasonal spatially distributed evapotranspiration fluxes at various scales and over large areas. In the arid western United States, water managers are challenged in balancing the high consumptive use of irrigated agriculture with competing urban and ecological uses of fresh water. Water managers from Irrigation Districts and Federal Agencies such as the US Bureau of Reclamation have a need for improved operational tools for the prediction of evapotranspiration and irrigation water demand on a five to ten day timeframe. The paper will present a hybrid model that couples the surface energy balance approach with a simple empirical reflectance-based crop coefficient model, for estimation and prediction of evapotranspiration over large agricultural areas. The model is applied to a rain-fed intensively cultivated agricultural area, close to Ames, Iowa during the summer of 2002. The satellite, airborne and ground fluxes were collected during the SMACEX 02 experiment. The model is run in both simulation and prediction mode and the derived latent heat fluxes are compared spatially and temporally to aircraft derived fluxes from the USU airborne system and ground measured fluxes at thirteen eddy covariance stations, using appropriate upwind footprint source area functions.

  3. Estimation of the Components of the Carbon and Water Budgets for Winter Wheat by Combining High Resolution Remote Sensing Data with a Crop Model

    NASA Astrophysics Data System (ADS)

    Veloso, A.; Ceschia, E.

    2014-12-01

    Croplands occupy more than one third of Earth's terrestrial surface contributing to climate change and also being impacted by those changes, since their production is conditioned by climatic conditions and water resources. It is thus essential to quantify and analyze the production and the main components of the carbon and water cycles for crop ecosystems. We propose here a regional modeling approach that combines: high spatial and temporal resolutions (HSTR) optical remote sensing data, a simple crop model and an extensive set of in-situ measurements for model's calibration and validation. The model, named SAFYE-CO2 (Simple Algorithm for Fluxes and Yield Estimates), is a daily time step model based on Monteith's light-use efficiency theory and coupled with a water budget module (FAO-56 method). SAFYE-CO2 estimates components of the carbon budget (gross primary production (GPP), ecosystem respiration (Reco), net ecosystem exchange (NEE), …) and of the crop water cycle (evaporation, transpiration, evapotranspiration (ETR) and soil water content) and also time courses of dry aboveground biomass and yield by assimilating Green Area Index (GAI) data obtained from HSTR satellite observations. For this work, we used a unique set of Formosat-2 and SPOT images acquired from 2006 to 2011 in southwest France. Crop and soil model parameters were set using both in-situ measurements and values found in the literature. Phenological parameters were calibrated by the GAI assimilation. The results indicate that the model correctly reproduces winter wheat biomass and yield production (relative error about 25%) for years with contrasted climatic conditions. The estimated net carbon flux components were overall in agreement with the flux measurements, presenting good correlations (R² about 0.9 for GPP, 0.77 for Reco and 0.84 for NEE). Regarding the ETR, a good correlation (R2 about 0.73) and satisfactory errors (RMSE about 0.47 mm.d-1) were found. Carbon and water budgets as well

  4. CO2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: estimates from flux tower measurements

    USGS Publications Warehouse

    Gilmanov, Tagir; Wylie, Bruce; Tieszen, Larry; Meyers, Tilden R.; Baron, Vern S.; Bernacchi, Carl J.; Billesbach, David P.; Burba, George G.; Fischer, Marc L.; Glenn, Aaron J.; Hanan, Niall P.; Hatfield, Jerry L.; Heuer, Mark W.; Hollinger, Steven E.; Howard, Daniel M.; Matamala, Roser; Prueger, John H.; Tenuta, Mario; Young, David G.

    2013-01-01

    We analyzed net CO2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σVPD. In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100 g CO2 m−2 year−1. The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  6. Parameterization of ALMANAC crop simulation model for non-irrigated dry bean in semi-arid temperate areas in Mexico

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Simulation models can be used to make management decisions when properly parameterized. This study aimed to parameterize the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) crop simulation model for dry bean in the semi-arid temperate areas of Mexico. The par...

  7. A STELLA Model to Estimate Water and Nitrogen Dynamics in a Short-Rotation Woody Crop Plantation.

    PubMed

    Ouyang, Ying; Zhang, Jiaen; Leininger, Theodor D; Frey, Brent R

    2015-01-01

    Although short-rotation woody crop biomass production technology has demonstrated a promising potential to supply feedstocks for bioenergy production, the water and nutrient processes in the woody crop planation ecosystem are poorly understood. In this study, a computer model was developed to estimate the dynamics of water and nitrogen (N) species (e.g., NH-N, NO-N, particulate organic N, and soluble organic N [SON]) in a woody crop plantation using STELLA (tructural hinking and xperiential earning aboratory with nimation) software. A scenario was performed to estimate diurnal and monthly water and N variations of a 1-ha mature cottonwood plantation over a 1-yr simulation period. A typical monthly variation pattern was found for soil water evaporation, leaf water transpiration, and root water uptake, with an increase from winter to summer and a decrease from summer to the following winter. Simulations further revealed that the rate of soil water evaporation was one order of magnitude lower than that of leaf water transpiration. In most cases, the relative monthly water loss rates could be expressed as evapotranspiration > root uptake > percolation > runoff. Leaching of NO-N and SON depended not only on soil N content but also on rainfall rate and duration. Leaching of NO-N from the cottonwood plantation was about two times higher than that of SON. The relative monthly rate of N leaching was NO-N > SON > NH-N. This study suggests that the STELLA model developed is a useful tool for estimating water and N dynamics from a woody crop plantation. PMID:25602335

  8. A STELLA Model to Estimate Water and Nitrogen Dynamics in a Short-Rotation Woody Crop Plantation.

    PubMed

    Ouyang, Ying; Zhang, Jiaen; Leininger, Theodor D; Frey, Brent R

    2015-01-01

    Although short-rotation woody crop biomass production technology has demonstrated a promising potential to supply feedstocks for bioenergy production, the water and nutrient processes in the woody crop planation ecosystem are poorly understood. In this study, a computer model was developed to estimate the dynamics of water and nitrogen (N) species (e.g., NH-N, NO-N, particulate organic N, and soluble organic N [SON]) in a woody crop plantation using STELLA (tructural hinking and xperiential earning aboratory with nimation) software. A scenario was performed to estimate diurnal and monthly water and N variations of a 1-ha mature cottonwood plantation over a 1-yr simulation period. A typical monthly variation pattern was found for soil water evaporation, leaf water transpiration, and root water uptake, with an increase from winter to summer and a decrease from summer to the following winter. Simulations further revealed that the rate of soil water evaporation was one order of magnitude lower than that of leaf water transpiration. In most cases, the relative monthly water loss rates could be expressed as evapotranspiration > root uptake > percolation > runoff. Leaching of NO-N and SON depended not only on soil N content but also on rainfall rate and duration. Leaching of NO-N from the cottonwood plantation was about two times higher than that of SON. The relative monthly rate of N leaching was NO-N > SON > NH-N. This study suggests that the STELLA model developed is a useful tool for estimating water and N dynamics from a woody crop plantation.

  9. Regional estimation of soil C stocks and CO2 emissions as influenced by cropping systems and soil type

    NASA Astrophysics Data System (ADS)

    Farina, Roberta; Marchetti, Alessandro; Di Bene, Claudia

    2015-04-01

    Soil organic matter (SOM) is of crucial importance for agricultural soil quality and fertility. At global level soil contains about three times the carbon stored in the vegetation and about twice that present in the atmosphere. Soil could act as source and sink of carbon, influencing the balance of CO2 concentration and consequently the global climate. The sink/source ratio depends on many factors that encompass climate, soil characteristics and different land management practices. Thus, the relatively large gross exchange of GHGs between atmosphere and soils and the significant stocks of carbon in soils, may have significant impact on climate and on soil quality. To quantify the dynamics of C induced by land cover change and the spatial and temporal dynamics of C sources and sinks at regional and, potentially, at national and global scales, we propose a methodology, based on a bio-physical model combined with a spatial explicit database to estimate C stock changes and emissions/removals. The study has been conducted in a pilot region in Italy (Apulia, Foggia province), considering the typical cropping systems of the area, namely rainfed cereals, tomato, vineyard and olives. For this purpose, the model RothC10N (Farina et al., 2013), that simulates soil C dynamics, has been modified to work directly in batch using data of climate, soil (over 290 georeferenced soil profiles), annual agriculture land use (1200 observations) The C inputs from crops have been estimated using statistics and data from literature. The model was run to equilibrium for each point of soil, in order to make all the data homogeneous in terms of time. The obtained data were interpolate with geostatisical procedures, obtaining a set of 30x30 km grid with the initial soil C. The new layer produced, together with soil and land use layers, were used for a long-term run (12 years). Results showed that olive groves and vineyards were able to stock a considerable amount of C (from 0.4 to 1.5 t ha-1 y

  10. Estimation of underground structure at Prambanan area, Yogyakarta, Indonesia

    SciTech Connect

    Thein, Pyi Soe; Pramumijoyo, Subagyo; Wilopo, Wahyu; Husein, Salahuddin; Setianto, Agung; Brotopuspito, Kirbani Sri; Kiyono, Junji

    2015-04-24

    In this study, we investigated the underground structure at Prambanan area, Yogyakarta. We performed single observations of microtremor at 124 sites in Prambanan area. The results enabled us to estimate the site-dependent shaking characteristics of earthquake ground motion. We also conducted 2-site bore holes investigation to gain a representative determination of the soil condition of subsurface structures in Prambanan. From the SPT of borehole observations, the prambanan area corresponds to relatively soil condition with Vs ≤ 298 m/s, the predominant periods due to horizontal vertical ratios (HVSRs) are in the range of 0.48 to 1.19 s and the frequency are in the range of 0.95 to 1.92 Hz. By making these observations, we can obtain a relationship between the predominant periods, frequency and distribution of the first layer thickness of the sediment.

  11. Rain volume estimation over areas using satellite and radar data

    NASA Technical Reports Server (NTRS)

    Doneaud, Andre A.; Vonderhaar, T. H.; Johnson, L. R.; Laybe, P.; Reinke, D.

    1987-01-01

    The analysis of 18 convective clusters demonstrates that the extension of the Area-Time-Integral (ATI) technique to the use of satellite data is possible. The differences of the internal structures of the radar reflectivity features, and of the satellite features, give rise to differences in estimating rain volumes by delineating area; however, by focusing upon the area integrated over the lifetime of the storm, it is suggested that some of the errors produced by the differences in the cloud geometries as viewed by radar or satellite are minimized. The results are good and future developments should consider data from different climatic regions and should allow for implementation of the technique in a general circulation model.

  12. Using FAO-56 model to estimate soil and crop water status: Application to a citrus orchard under regulated deficit irrigation

    NASA Astrophysics Data System (ADS)

    Provenzano, Giuseppe; Gonzàles-Altozano, Pablo; Manzano-Juàrez, Juan; Rallo, Giovanni

    2015-04-01

    Agro-hydrological models allow schematizing exchange processes in the soil-plant-atmosphere continuum (SPAC) on a wide range of spatial and temporal scales. Each section of the SPAC system is characterized by complex behaviours arising, for instance, the adaptive plant strategies in response to soil water deficit conditions. Regulated deficit irrigation (RDI) has been considered as one of the potential strategies for sustainable crop production in regions characterized by water scarcity. Moreover, reducing water supply at certain growth stages can improve water use efficiency (WUE) and quality of productions, without affecting significantly crop yield. Environmental policy requires to improve WUE in crops with high water requirements, so that it is necessary to identify easy-to-use tools aimed at irrigation water saving strategies, without the need of tedious and time consuming experiments. Accurate evaluation of crop water status and actual transpiration plays a key role in irrigation scheduling under RDI, in order to avoid that water stress becomes too severe and detrimental to yield and fruit quality. Objective of the research was to assess the suitability of FAO56 agro-hydrological model (Allen et al., 1998) on citrus orchards under different water deficit conditions, to estimate soil and crop water status. The ability of the model to predict actual crop water stress was evaluated based on the temporal dynamic of simulated relative transpirations and on the similarities with the corresponding dynamic of measured midday stem water potentials, MSWP. During dry periods, simulated relative crop transpiration was correlated to MSWP with the aim to assess the model ability to predict crop water stress and to identify "plant-based" irrigation scheduling parameters. Experiments were carried out during three years from 2009 and 2011 in Senyera (39° 3' 35.4" N, 0° 30' 28.2" W), Spain, in a commercial orchard planted with Navelina/Cleopatra citrus trees. Three RDI

  13. Small area estimation for estimating the number of infant mortality in West Java, Indonesia

    NASA Astrophysics Data System (ADS)

    Anggreyani, Arie; Indahwati, Kurnia, Anang

    2016-02-01

    Demographic and Health Survey Indonesia (DHSI) is a national designed survey to provide information regarding birth rate, mortality rate, family planning and health. DHSI was conducted by BPS in cooperation with National Population and Family Planning Institution (BKKBN), Indonesia Ministry of Health (KEMENKES) and USAID. Based on the publication of DHSI 2012, the infant mortality rate for a period of five years before survey conducted is 32 for 1000 birth lives. In this paper, Small Area Estimation (SAE) is used to estimate the number of infant mortality in districts of West Java. SAE is a special model of Generalized Linear Mixed Models (GLMM). In this case, the incidence of infant mortality is a Poisson distribution which has equdispersion assumption. The methods to handle overdispersion are binomial negative and quasi-likelihood model. Based on the results of analysis, quasi-likelihood model is the best model to overcome overdispersion problem. The basic model of the small area estimation used basic area level model. Mean square error (MSE) which based on resampling method is used to measure the accuracy of small area estimates.

  14. Exploring the Usefulness of MISR-HR Products to Estimate Maize Crop Extent and Using Field Evidence to Evaluate the Results in South Africa's Free State Province

    NASA Astrophysics Data System (ADS)

    Verstraete, M. M.; Knox, N. M.; Hunt, L. A.; Kleyn, L.

    2014-12-01

    The MISR instrument on NASA's Terra platform has been operating for almost 15 years. Standard products are generated at a spatial resolution of 1.1 km or coarser, but a recently developed method to re-analyze the Level-1B2 data allows the retrieval of biogeophysical products at the native spatial resolution of the instrument (275 m). This development opens new opportunities to better address issues such as the management of agricultural production and food security. South African maize production is of great economic and social importance, not only nationally, but on the global market too, being one of the top ten maize producing countries. Seasonal maize production statistics are currently based on a combination of field measurements and estimates derived from manually digitizing high resolution imagery from the SPOT satellite. The field measurements are collected using the Producer Independent Crop Estimate System (PICES) developed by Crop Estimates Committee of the Department of Agriculture, Forestry and Fisheries. There is a strong desire to improve the quality of these statistics, to generate those earlier, and to automate the process to encompass larger areas. This paper will explore the feasibility of using the MISR-HR spectral and directional products, combined with the finer spatial resolution and the relatively frequent coverage afforded by that instrument, to address these needs. The study area is based in the Free State, South Africa, one of the primary maize growing areas in the country, and took place during the 2012-2013 summer growing season. The significance of the outcomes will be evaluated in the context of the 14+ years of available MISR data.

  15. Penman-Monteith approaches for estimating crop evapotranspiration in screenhouses--a case study with table-grape.

    PubMed

    Pirkner, Moran; Dicken, Uri; Tanny, Josef

    2014-07-01

    In arid and semi-arid regions many crops are grown under screens or in screenhouses to protect them from excessive radiation, strong winds, hailstorms and insects, and to reduce crop water requirements. Screens modify the crop microclimate, which means that it is necessary to accurately estimate crop water use under screens in order to improve the irrigation management and thereby increase water-use efficiency. The goal of the present study was to develop a set of calibrated relationships between inside and outside climatic variables, which would enable growers to predict crop water use under screens, based on standard external meteorological measurements and evapotranspiration (ET) models. Experiments were carried out in the Jordan Valley region of eastern Israel in a table-grape vineyard that was covered with a transparent screen providing 10% shading. An eddy covariance system was deployed in the middle of the vineyard and meteorological variables were measured inside and outside the screenhouse. Two ET models were evaluated: a classical Penman-Monteith model (PM) and a Penman-Monteith model modified for screenhouse conditions by the inclusion of an additional boundary-layer resistance (PMsc). Energy-balance closure analysis, presented as a linear relation between half-hourly values of available and consumed energy (1,344 data points), yielded the regression Y=1.05X-9.93 (W m(-2)), in which Y=sum of latent and sensible heat fluxes, and X=net radiation minus soil heat flux, with R2=0.81. To compensate for overestimation of the eddy fluxes, ET was corrected by forcing the energy balance closure. Average daily ET under the screen was 5.4±0.54 mm day(-1), in general agreement with the model estimates and the applied irrigation. The results showed that measured ET under the screen was, on average, 34% lower than that estimated outside, indicating significant potential water saving through screening irrigated vineyards. The PM model was somewhat more accurate than

  16. A one-layer satellite surface energy balance for estimating evapotranspiration rates and crop water stress indexes.

    PubMed

    Barbagallo, Salvatore; Consoli, Simona; Russo, Alfonso

    2009-01-01

    Daily evapotranspiration fluxes over the semi-arid Catania Plain area (Eastern Sicily, Italy) were evaluated using remotely sensed data from Landsat Thematic Mapper TM5 images. A one-source parameterization of the surface sensible heat flux exchange using satellite surface temperature has been used. The transfer of sensible and latent heat is described by aerodynamic resistance and surface resistance. Required model inputs are brightness, temperature, fractional vegetation cover or leaf area index, albedo, crop height, roughness lengths, net radiation, air temperature, air humidity and wind speed. The aerodynamic resistance (r(ah)) is formulated on the basis of the Monin-Obukhov surface layer similarity theory and the surface resistance (r(s)) is evaluated from the energy balance equation. The instantaneous surface flux values were converted into evaporative fraction (EF) over the heterogeneous land surface to derive daily evapotranspiration values. Remote sensing-based assessments of crop water stress (CWSI) were also made in order to identify local irrigation requirements. Evapotranspiration data and crop coefficient values obtained from the approach were compared with: (i) data from the semi-empirical approach "K(c) reflectance-based", which integrates satellite data in the visible and NIR regions of the electromagnetic spectrum with ground-based measurements and (ii) surface energy flux measurements collected from a micrometeorological tower located in the experiment area. The expected variability associated with ET flux measurements suggests that the approach-derived surface fluxes were in acceptable agreement with the observations.

  17. A One-Layer Satellite Surface Energy Balance for Estimating Evapotranspiration Rates and Crop Water Stress Indexes

    PubMed Central

    Barbagallo, Salvatore; Consoli, Simona; Russo, Alfonso

    2009-01-01

    Daily evapotranspiration fluxes over the semi-arid Catania Plain area (Eastern Sicily, Italy) were evaluated using remotely sensed data from Landsat Thematic Mapper TM5 images. A one-source parameterization of the surface sensible heat flux exchange using satellite surface temperature has been used. The transfer of sensible and latent heat is described by aerodynamic resistance and surface resistance. Required model inputs are brightness, temperature, fractional vegetation cover or leaf area index, albedo, crop height, roughness lengths, net radiation, air temperature, air humidity and wind speed. The aerodynamic resistance (rah) is formulated on the basis of the Monin-Obukhov surface layer similarity theory and the surface resistance (rs) is evaluated from the energy balance equation. The instantaneous surface flux values were converted into evaporative fraction (EF) over the heterogeneous land surface to derive daily evapotranspiration values. Remote sensing-based assessments of crop water stress (CWSI) were also made in order to identify local irrigation requirements. Evapotranspiration data and crop coefficient values obtained from the approach were compared with: (i) data from the semi-empirical approach “Kc reflectance-based”, which integrates satellite data in the visible and NIR regions of the electromagnetic spectrum with ground-based measurements and (ii) surface energy flux measurements collected from a micrometeorological tower located in the experiment area. The expected variability associated with ET flux measurements suggests that the approach-derived surface fluxes were in acceptable agreement with the observations. PMID:22389585

  18. A remote-sensing driven tool for estimating crop stress and yields

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Biophysical crop simulation models are normally forced with precipitation data recorded with either gages or ground-based radar. However, ground based recording networks are not available at spatial and temporal scales needed to drive the models at many critical places on earth. An alternative would...

  19. Hyperspectral remote sensing estimation of crop residue cover: Soil mineralogy, surface conditions, and their effects

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Conservation tillage practices can enhance soil organic carbon content (SOC), improve soil structure, and reduce erosion. However, direct assessment of tillage practice for monitoring SOC change over large regions is difficult. Remote sensing of crop residue cover (CRC) can help assess tillage pra...

  20. Estimating plant available water for general crop simulations in ALMANAC/APEX/EPIC/SWAT

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Process-based simulation models ALMANAC/APEX/EPIC/SWAT contain generalized plant growth subroutines to predict biomass and crop yield. Environmental constraints typically restrict plant growth and yield. Water stress is often an important limiting factor; it is calculated as the sum of water use f...

  1. Quantitative estimation of the fluorescent parameters for crop leaves with the Bayesian inversion

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In this study, the fluorescent parameters of crop leaves were retrieved from the leaf hyperspectral measurements by inverting the FluorMODleaf model, which is a leaf-level fluorescence model that is based on the widely used and validated PROSPECT (leaf optical properties) model and can simulate the ...

  2. The large area crop inventory experiment: A major demonstration of space remote sensing

    NASA Technical Reports Server (NTRS)

    Macdonald, R. B.; Hall, F. G.

    1977-01-01

    Strategies are presented in agricultural technology to increase the resistance of crops to a wider range of meteorological conditions in order to reduce year-to-year variations in crop production. Uncertainties in agricultral production, together with the consumer demands of an increasing world population, have greatly intensified the need for early and accurate annual global crop production forecasts. These forecasts must predict fluctuation with an accuracy, timeliness and known reliability sufficient to permit necessary social and economic adjustments, with as much advance warning as possible.

  3. Estimating soybean cultivated area using multi-source remotely sensed data (Invited)

    NASA Astrophysics Data System (ADS)

    Hansen, M.; Stehman, S.; Adusei, B.; King, L. M.; Noel, J.; Ernst, C. L.; Potapov, P.

    2013-12-01

    National-scale soybean cultivated area is estimated using a probability-based sampling method and the integrated use of MODIS, Landsat and RapidEye data. The study areas include the United States, Brazil and Argentina, which combined account for over 80% of global soybean production. Indicator maps of percent soybean using MODIS are used to stratify agricultural regions into strata of high, medium and low soybean cover. Within each stratum, 40km by 40km samples are analyzed using time-series Landsat and peak growing season RapidEye data. Per pixel maps of soybean/no soybean are made per sample block and per stratum means calculated. A regression estimator is then run using the per block mapped estimate versus a current year MODIS estimate. Initial results for the United States for 2011 result in an area estimate of 215,000km2 (SE=6,000 km2). Comparison of our 30m Landsat soy classification with the NASS Cropland Data Layer (CDL) soybean map shows a strong overall agreement of 91.3% and a good linear relationship of y=.67x +.75 across all samples. CDL soybean area estimate over the same block population yields 275,000km2 (SE=9,000 km2). Our independently-derived 5m RapidEye classified soybean product was compared to both our Landsat characterizations as well as the CDL map. The Landsat classification had balanced commission and omission errors in terms of agreement with RapidEye, and a resulting 1:1 relationship. The CDL overestimated soybean compared to RapidEye with more commission than omission errors and a 1.14:1 ratio. Results for Argentina and Brazil will also be presented and indicate a robust method for estimating cultivated area of crop type that can be replicated for major growing regions globally. Discrepancies with national statistics are expected and must be validated, for example using field data or other information such as the RapidEye or other higher spatial resolution data sets.

  4. Spectral estimation of green leaf area index of oats

    NASA Technical Reports Server (NTRS)

    Best, R. G.; Harlan, J. C.

    1985-01-01

    Green leaf area index (LAI) is a measure of vegetative growth and development and is frequently used as an input parameter in yield estimation and evapotranspiration models. Extensive destructive sampling is usually required to achieve accurate estimates of green LAI in natural situations. In this investigation, a statistical modeling approach was used to predict the green LAI of oats from bidirectional reflectance data collected with multiband radiometers. Stepwise multiple regression models based on two sets of spectral reflectance factors accounted for 73 percent and 65 percent of the variance in green LAI of oats. Exponential models of spectral data transformations of greenness, normalized difference, and near-infrared/red ratio accounted for more of the variance in green LAI than the multiple regression models.

  5. Area-to-point parameter estimation with geographically weighted regression

    NASA Astrophysics Data System (ADS)

    Murakami, Daisuke; Tsutsumi, Morito

    2015-07-01

    The modifiable areal unit problem (MAUP) is a problem by which aggregated units of data influence the results of spatial data analysis. Standard GWR, which ignores aggregation mechanisms, cannot be considered to serve as an efficient countermeasure of MAUP. Accordingly, this study proposes a type of GWR with aggregation mechanisms, termed area-to-point (ATP) GWR herein. ATP GWR, which is closely related to geostatistical approaches, estimates the disaggregate-level local trend parameters by using aggregated variables. We examine the effectiveness of ATP GWR for mitigating MAUP through a simulation study and an empirical study. The simulation study indicates that the method proposed herein is robust to the MAUP when the spatial scales of aggregation are not too global compared with the scale of the underlying spatial variations. The empirical studies demonstrate that the method provides intuitively consistent estimates.

  6. Tracer Testing for Estimating Heat Transfer Area in Fractured Reservoirs

    SciTech Connect

    Pruess, Karsten; van Heel, Ton; Shan, Chao

    2004-05-12

    A key parameter governing the performance and life-time of a Hot Fractured Rock (HFR) reservoir is the effective heat transfer area between the fracture network and the matrix rock. We report on numerical modeling studies into the feasibility of using tracer tests for estimating heat transfer area. More specifically, we discuss simulation results of a new HFR characterization method which uses surface-sorbing tracers for which the adsorbed tracer mass is proportional to the fracture surface area per unit volume. Sorption in the rock matrix is treated with the conventional formulation in which tracer adsorption is volume-based. A slug of solute tracer migrating along a fracture is subject to diffusion across the fracture walls into the adjacent rock matrix. Such diffusion removes some of the tracer from the fluid in the fractures, reducing and retarding the peak in the breakthrough curve (BTC) of the tracer. After the slug has passed the concentration gradient reverses, causing back-diffusion from the rock matrix into the fracture, and giving rise to a long tail in the BTC of the solute. These effects become stronger for larger fracture-matrix interface area, potentially providing a means for estimating this area. Previous field tests and modeling studies have demonstrated characteristic tailing in BTCs for volatile tracers in vapor-dominated reservoirs. Simulated BTCs for solute tracers in single-phase liquid systems show much weaker tails, as would be expected because diffusivities are much smaller in the aqueous than in the gas phase, by a factor of order 1000. A much stronger signal of fracture-matrix interaction can be obtained when sorbing tracers are used. We have performed simulation studies of surface-sorbing tracers by implementing a model in which the adsorbed tracer mass is assumed proportional to the fracture-matrix surface area per unit volume. The results show that sorbing tracers generate stronger tails in BTCs, corresponding to an effective

  7. Image based remote sensing method for modeling black-eyed beans ( Vigna unguiculata) Leaf Area Index (LAI) and Crop Height (CH) over Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, Giorgos; Fasoula, Dionysia; Hadjimitsis, Michael; Skevi Perdikou, P.; Hadjimitsis, Diofantos G.

    2013-03-01

    In this paper, Leaf Area Index (LAI) and Crop Height (CH) are modeled to the most known spectral vegetation index — NDVI — using remotely sensed data. This approach has advantages compared to the classic approaches based on a theoretical background. A GER-1500 field spectro-radiometer was used in this study in order to retrieve the necessary spectrum data for estimating a spectral vegetation index (NDVI), for establishing a semiempirical relationship between black-eyed beans' canopy factors and remotely sensed data. Such semi-empirical models can be used then for agricultural and environmental studies. A field campaign was undertaken with measurements of LAI and CH using the Sun-Scan canopy analyzer, acquired simultaneously with the spectroradiometric (GER1500) measurements between May and June of 2010. Field spectroscopy and remotely sensed imagery have been combined and used in order to retrieve and validate the results of this study. The results showed that there are strong statistical relationships between LAI or CH and NDVI which can be used for modeling crop canopy factors (LAI, CH) to remotely sensed data. The model for each case was verified by the factor of determination. Specifically, these models assist to avoid direct measurements of the LAI and CH for all the dates for which satellite images are available and support future users or future studies regarding crop canopy parameters.

  8. Image based remote sensing method for modeling black-eyed beans (Vigna unguiculata) Leaf Area Index (LAI) and Crop Height (CH) over Cyprus

    NASA Astrophysics Data System (ADS)

    Papadavid, Giorgos; Fasoula, Dionysia; Hadjimitsis, Michael; Skevi Perdikou, P.; Hadjimitsis, Diofantos

    2013-03-01

    In this paper, Leaf Area Index (LAI) and Crop Height (CH) are modeled to the most known spectral vegetation index — NDVI — using remotely sensed data. This approach has advantages compared to the classic approaches based on a theoretical background. A GER-1500 field spectro-radiometer was used in this study in order to retrieve the necessary spectrum data for estimating a spectral vegetation index (NDVI), for establishing a semiempirical relationship between black-eyed beans' canopy factors and remotely sensed data. Such semi-empirical models can be used then for agricultural and environmental studies. A field campaign was undertaken with measurements of LAI and CH using the Sun-Scan canopy analyzer, acquired simultaneously with the spectroradiometric (GER1500) measurements between May and June of 2010. Field spectroscopy and remotely sensed imagery have been combined and used in order to retrieve and validate the results of this study. The results showed that there are strong statistical relationships between LAI or CH and NDVI which can be used for modeling crop canopy factors (LAI, CH) to remotely sensed data. The model for each case was verified by the factor of determination. Specifically, these models assist to avoid direct measurements of the LAI and CH for all the dates for which satellite images are available and support future users or future studies regarding crop canopy parameters.

  9. Rain volume estimation over areas using satellite and radar data

    NASA Technical Reports Server (NTRS)

    Doneaud, A. A.; Vonderhaar, T. H.

    1985-01-01

    The feasibility of rain volume estimation over fixed and floating areas was investigated using rapid scan satellite data following a technique recently developed with radar data, called the Area Time Integral (ATI) technique. The radar and rapid scan GOES satellite data were collected during the Cooperative Convective Precipitation Experiment (CCOPE) and North Dakota Cloud Modification Project (NDCMP). Six multicell clusters and cells were analyzed to the present time. A two-cycle oscillation emphasizing the multicell character of the clusters is demonstrated. Three clusters were selected on each day, 12 June and 2 July. The 12 June clusters occurred during the daytime, while the 2 July clusters during the nighttime. A total of 86 time steps of radar and 79 time steps of satellite images were analyzed. There were approximately 12-min time intervals between radar scans on the average.

  10. Wheat cultivation: Identification and estimation of areas using LANDSAT data

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Mendonca, F. J.; Cottrell, D. A.; Tardin, A. T.; Lee, D. C. L.; Shimabukuro, Y. E.; Moreira, M. A.; Delimaefernandocelsosoaresmaia, A. M.

    1981-01-01

    The feasibility of using automatically processed multispectral data obtained from LANDSAT to identify wheat and estimate the areas planted with this grain was investigated. Three 20 km by 40 km segments in a wheat growing region of Rio Grande do Sul were aerially photographed using type 2443 Aerochrome film. Three maps corresponding to each segment were obtained from the analysis of the photographs which identified wheat, barley, fallow land, prepared soil, forests, and reforested land. Using basic information about the fields and maps made from the photographed areas, an automatic classification of wheat was made using MSS data from two different periods: July to September and July to October 1979. Results show that orbital data is not only useful in characterizing the growth of wheat, but also provides information of the intensity and extent of adverse climate which affects cultivation. The temporal and spatial characteristics of LANDSAR data are also demonstrated.

  11. Effects of crop growth and development on regional climate: a case study over East Asian monsoon area

    NASA Astrophysics Data System (ADS)

    Chen, Feng; Xie, Zhenghui

    2012-06-01

    In this study, the CERES phenological growth and development functions were implemented into the regional climate model, RegCM3 to give a model denoted as RegCM3_CERES. This model was used to represent interactions between regional climate and crop growth processes. The effects of crop growth and development processes on regional climate were then studied based on two 20-year simulations over the East Asian monsoon area conducted using the original regional climate model RegCM3, and the coupled RegCM3_CERES model. The numerical experiments revealed that incorporating the crop growth and development processes into the regional climate model reduced the root mean squared error of the simulated precipitation by 2.2-10.7% over north China, and the simulated temperature by 5.5-30.9% over the monsoon region in eastern China. Comparison of the simulated results obtained using RegCM3_CERES and RegCM3 showed that the most significant changes associated with crop modeling were the changes in leaf area index which in turn modify the aspects of surface energy and water partitions and lead to moderate changes in surface temperature and, to some extent, rainfall. Further analysis revealed that a robust representation of seasonal changes in plant growth and developmental processes in the regional climate model changed the surface heat and moisture fluxes by modifying the vegetation characteristics, and that these differences in simulated surface fluxes resulted in different structures of the boundary layer and ultimately affected the convection. The variations in leaf area index and fractional vegetation cover changed the distribution of evapotranspiration and heat fluxes, which could potentially lead to anomalies in geopotential height, and consequently influenced the overlying atmospheric circulation. These changes would result in redistribution of the water and energy through advection. Nevertheless, there are significant uncertainties in modeling how monsoon dynamics responds

  12. Research in satellite-aided crop inventory and monitoring

    NASA Technical Reports Server (NTRS)

    Erickson, J. D.; Dragg, J. L.; Bizzell, R. M.; Trichel, M. C. (Principal Investigator)

    1982-01-01

    Automated information extraction procedures for analysis of multitemporal LANDSAT data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develope and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed.

  13. Estimation of stand-level leaf area for boreal bryophytes.

    PubMed

    Bond-Lamberty, Ben; Gower, Stith T

    2007-04-01

    Bryophytes dominate the carbon and nitrogen cycling of many poorly drained terrestrial ecosystems and are important in the vegetation-atmosphere exchange of carbon and water, yet few studies have estimated their leaf area at the stand scale. This study quantified the bryophyte-specific leaf area (SLA) and leaf area index (LAI) in a group of different-aged boreal forest stands in well and poorly drained soils. Species-specific SLA (for three feather mosses, four Sphagnum spp. and Aulacomnium palustre mixed with Tomentypnum nitens) was assessed by determining the projected area using a flatbed scanner and cross-sectional geometry using a dissecting microscope. The hemisurface leaf area was computed as the product of SLA and live biomass and was scaled by coverage data collected at all stands. Pleurozium schreberi dominated the spatial coverage, biomass and leaf area in the well-drained stands, particularly the oldest, while S. fuscum and A. palustre were important in the poorly drained stands. Live moss biomass ranged from 47 to 230 g m(-2) in the well-drained stands dominated by feather mosses and from 102 to 228 g m(-2) in the poorly drained stands. Bryophyte SLA varied between 135 and 473 cm(2) g(-1), for A. palustre and S. capillifolium, respectively. SLA was strongly and significantly affected by bryophyte species, but did not vary between stands; in general, there was no significant difference between the SLA of non-Sphagnum mosses. Bryophyte LAI increased with stand age, peaking at 3.1 and 3.7 in the well and poorly drained stands, respectively; this represented approximately 40% of the overstory LAI in the well-drained stands and 100-1,000% in the poorly drained stands, underscoring the important role bryophytes play in the water and carbon budgets of these boreal forests.

  14. Estimation of Some Bio-Physical Indicators for Sustainable Crop Production in the Eastern Nile Basin of Sudan Using Landsat-8 Imagery and SEBAL Model

    NASA Astrophysics Data System (ADS)

    Guma Biro Turk, Khalid

    2016-07-01

    Crop production under modern irrigation systems require unique management at field level and hence better utilization of agricultural inputs and water resources. This study aims to make use of remote sensing (RS) data and the surface energy balance algorithm for land (SEBAL) to improve the on-farm management. The study area is located in the Eastern part of the Blue Nile River about 60 km south of Khartoum, Sudan. Landsat-8 data were used to estimate a number of bio-physical indicators during the growing season of the year 2014/2015. Accordingly, in-situ weather data and SEBAL model were applied to calculate: the reference (ET0), actual (ETa) and potential (ETp) evapotranspiration, soil moisture (SM), crop factor (kc), nitrogen (N), biomass production (BP) and crop water productivity (CWP). Results revealed that ET0 showed steady variation throughout the year, varying from 5 to 7 mm/day. However, ETa and ETp showed clear temporal variation attributed to frequent cutting of the alfalfa, almost monthly. The BP of the alfalfa was observed to be high when there is no cutting activates were made before the image acquisition date. Nevertheless the CWP trends are following the biomass production ones, low when there is no biomass and high when the biomass is high. The application of SEBAL model within the study area using the Landsat-8 imagery indicates that it's possible to produce field-based bio-physical indicators, which can be useful in monitoring and managing the field during the growing season. However, a cross-calibration with the in-situ data should be considered in order to maintain the spatial variability within the field. Keywords: Bio-physical Indicators; Remote Sensing; SEBAL; Landsat-8; Eastern Nile Basin

  15. Use of landsat thematic mapper data to identify crop types and estimate irrigated acreage, Uvalde and Medina counties, Texas, 1991

    USGS Publications Warehouse

    Raymond, L.H.; McFarlane, S.I.

    1994-01-01

    The total number of acres of irrigated crops estimated using Landsat TM data was about 9 percent lower in Uvalde County and about 13 percent lower in Medina County than the number of acres calculated from data reported by the U.S. Department of Agriculture, Agricultural Stabilization and Conservation Service (ASCS). The total quantity of water pumped from the Edwards aquifer for irrigation in the two counties in 1991, about 83,000 acre-feet, was about 5 percent greater than the quantity calculated from data reported by the ASCS.

  16. Digital cover photography for estimating leaf area index (LAI) in apple trees using a variable light extinction coefficient.

    PubMed

    Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

    2015-01-28

    Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAI(D)), which was compared with LAI estimated by the proposed digital photography method (LAI(M)). Results showed that the LAI(M) was able to estimate LAI(D) with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (f(f)) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.

  17. Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

    PubMed Central

    Poblete-Echeverría, Carlos; Fuentes, Sigfredo; Ortega-Farias, Samuel; Gonzalez-Talice, Jaime; Yuri, Jose Antonio

    2015-01-01

    Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions. PMID:25635411

  18. Assessing changes to South African maize production areas in 2055 using empirical and process-based crop models

    NASA Astrophysics Data System (ADS)

    Estes, L.; Bradley, B.; Oppenheimer, M.; Beukes, H.; Schulze, R. E.; Tadross, M.

    2010-12-01

    Rising temperatures and altered precipitation patterns associated with climate change pose a significant threat to crop production, particularly in developing countries. In South Africa, a semi-arid country with a diverse agricultural sector, anthropogenic climate change is likely to affect staple crops and decrease food security. Here, we focus on maize production, South Africa’s most widely grown crop and one with high socio-economic value. We build on previous coarser-scaled studies by working at a finer spatial resolution and by employing two different modeling approaches: the process-based DSSAT Cropping System Model (CSM, version 4.5), and an empirical distribution model (Maxent). For climate projections, we use an ensemble of 10 general circulation models (GCMs) run under both high and low CO2 emissions scenarios (SRES A2 and B1). The models were down-scaled to historical climate records for 5838 quinary-scale catchments covering South Africa (mean area = 164.8 km2), using a technique based on self-organizing maps (SOMs) that generates precipitation patterns more consistent with observed gradients than those produced by the parent GCMs. Soil hydrological and mechanical properties were derived from textural and compositional data linked to a map of 26422 land forms (mean area = 46 km2), while organic carbon from 3377 soil profiles was mapped using regression kriging with 8 spatial predictors. CSM was run using typical management parameters for the several major dryland maize production regions, and with projected CO2 values. The Maxent distribution model was trained using maize locations identified using annual phenology derived from satellite images coupled with airborne crop sampling observations. Temperature and precipitation projections were based on GCM output, with an additional 10% increase in precipitation to simulate higher water-use efficiency under future CO2 concentrations. The two modeling approaches provide spatially explicit projections of

  19. Economic evaluation of crop acreage estimation by multispectral remote sensing. [Michigan

    NASA Technical Reports Server (NTRS)

    Manderscheid, L. V.; Nalepka, R. F. (Principal Investigator); Myers, W.; Safir, G.; Ilhardt, D.; Morgenstern, J. P.; Sarno, J.

    1976-01-01

    The author has identified the following significant results. Photointerpretation of S190A and S190B imagery showed significantly better resolution with the S190B system. A small tendancy to underestimate acreage was observed. This averaged 6 percent and varied with field size. The S190B system had adequate resolution for acreage measurement but the color film did not provide adequate contrast to allow detailed classification of ground cover from imagery of a single date. In total 78 percent of the fields were correctly classified but with 56 percent correct for the major crop, corn.

  20. Preliminary evaluation of the Environmental Research Institute of Michigan crop calendar shift algorithm for estimation of spring wheat development stage. [North Dakota, South Dakota, Montana, and Minnesota

    NASA Technical Reports Server (NTRS)

    Phinney, D. E. (Principal Investigator)

    1980-01-01

    An algorithm for estimating spectral crop calendar shifts of spring small grains was applied to 1978 spring wheat fields. The algorithm provides estimates of the date of peak spectral response by maximizing the cross correlation between a reference profile and the observed multitemporal pattern of Kauth-Thomas greenness for a field. A methodology was developed for estimation of crop development stage from the date of peak spectral response. Evaluation studies showed that the algorithm provided stable estimates with no geographical bias. Crop development stage estimates had a root mean square error near 10 days. The algorithm was recommended for comparative testing against other models which are candidates for use in AgRISTARS experiments.

  1. Empirically-Based Crop Insurance for China: A Pilot Study in the Down-middle Yangtze River Area of China

    NASA Astrophysics Data System (ADS)

    Wang, Erda; Yu, Yang; Little, Bertis B.; Chen, Zhongxin; Ren, Jianqiang

    Factors that caused slow growth in crop insurance participation and its ultimate failure in China were multi-faceted including high agricultural production risk, low participation rate, inadequate public awareness, high loss ratio, insufficient and interrupted government financial support. Thus, a clear and present need for data driven analyses and empirically-based risk management exists in China. In the present investigation, agricultural production data for two crops (corn, rice) in five counties in Jiangxi Province and Hunan province for design of a pilot crop insurance program in China. A crop insurance program was designed which (1) provides 75% coverage, (2) a 55% premium rate reduction for the farmer compared to catastrophic coverage most recently offered, and uses the currently approved governmental premium subsidy level. Thus a safety net for Chinese farmers that help maintain agricultural production at a level of self-sufficiency that costs less than half the current plans requires one change to the program: ≥80% of producers must participate in an area.

  2. Flood Damage Estimation of Coastal Area Considering Climate Change

    NASA Astrophysics Data System (ADS)

    Lee, J.; Kim, K.; Choi, C.; Han, D.; Kim, H. S.

    2015-12-01

    There are various researches to respond to the natural disasters efficiently such as floods caused by climate change. Most of the studies have assessed the impact of climate change on floods by the increase of future rainfall and the sea level rise separately. However, we have to consider the effects of the combined floods by future heavy rainfall and sea level rise. This means the urban floods in coastal area can be occurred due to the combined inundation by overflow of urban drainage system and by sea level rise. Then we can estimate the flood damage from the combined floods due to the climate change. Hence, this study selected Taehwa River basin, Korea which flows from the west to the east and extends to Ulsan bay. This study analysed on the influence of hydrologic alteration in the coastal area by considering the sea level rise as well as the future precipitation according to climate change. It is prepared the flood inundation map which is related to the increase of precipitation and sea level for assuring how the sea level rise effects on the coastal area caused by the climate change, and the flood damage assessment is estimated to compare the hydrologic alteration quantitatively. The study result showed that flood level in the channel flows to the mouth rose as the water surface elevation rose due to the rise in sea level. In addition, the extent of increase in flood level caused by sea level rise was greater at a location nearer the outlet and it was smaller at a place farther from the outlet. It could be verified that the change of the inundation depth and damage area caused by the rise in sea level can have an effect on the flood damage assessment. It is important factor to analyse not only the increase of precipitation cuased of climate change in coastal rivers but also the change of rise in sea level, the flood water level, the flood inundation and the flood damage assessment. The result of this study could be used as basic data for creating technology

  3. Multi-sensor merging techniques for improving burned area estimates

    NASA Astrophysics Data System (ADS)

    Bradley, A.; Tansey, K.; Chuvieco, E.

    2012-04-01

    The ESA Climate Change Initiative (CCI) aims to create a set of Essential Climate Variables (ECV) to assist climate modellers. One of these is the fire ECV, a product in line with typical requirements of climate, vegetation and ecological modellers investigated by the fire ECV project and documented in the fire product specification document. The product is derived from burned area estimates of three sensors, SPOT VEGETATION (SPOT-VGT), the Along-Track Scanning Radiometer (ATSR) series, and the MEdium Resolution Imaging Spectrometer at Full ReSolution (MERIS FRS). This abstract is concerned with the final stage in the production of the fire product, merging of the burned area estimates from the three sensors into two products. The two products are created at monthly time steps, the pixel (1km) and the aggregated grid product (0.5° and 0.25°). The pixel product contains information on sensors detecting the burn, date of burn detection, confidence of the burn and land cover statistics. The grid product contains aggregated information on burned area totals and proportion, major land cover burned, heterogeneity of burning in the grid cell, confidence and cloud cover levels. The method used to create these products needs to allow for time series gaps due to multiple sensor combinations and different orbital and swath characteristics and comprises a combination statistical, selective, stratification and fusion methods common to the satellite remote sensing community. The method is in three stages, first a combined merge of sensors in the same 1km resolution. The earliest date of detection is recorded and the sensor that performs the best over a particular vegetation type is taken as the most reliable confidence level. The second part involves fusion of the 300 m MERIS FRS data allowing confidence levels and burn dates to be reported to a finer resolution. To allow for MERIS FRS pixels that cross adjacent 1km pixels from the first step the fusion is carried out at 100 m

  4. Benefit Estimates of Terminal Area Productivity Program Technologies

    NASA Technical Reports Server (NTRS)

    Hemm, Robert; Shapiro, Gerald; Lee, David; Gribko, Joana; Glaser, Bonnie

    1999-01-01

    This report documents benefit analyses for the NASA Terminal Area Technology (TAP) technology programs. Benefits are based on reductions in arrival delays at ten major airports over the 10 years from 2006 through 2015. Detailed analytic airport capacity and delay models were constructed to produce the estimates. The goal of TAP is enable good weather operations tempos in all weather conditions. The TAP program includes technologies to measure and predict runway occupancy times, reduce runway occupancy times in bad weather, accurately predict wake vortex hazards, and couple controller automation with aircraft flight management systems. The report presents and discusses the estimate results and describes the models. Three appendixes document the model algorithms and discuss the input parameters selected for the TAP technologies. The fourth appendix is the user's guide for the models. The results indicate that the combined benefits for all TAP technologies at all 10 airports range from $550 to $650 million per year (in constant 1997 dollars). Additional benefits will accrue from reductions in departure delays. Departure delay benefits are calculated by the current models.

  5. Worldwide Historical Estimates of Leaf Area Index, 1932-2000

    NASA Technical Reports Server (NTRS)

    Scurlock, J. M. O.; Asner, G. P.; Gower, S. T.

    2001-01-01

    Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 and other vegetation parameters. The LA1 data are linked to a bibliography of over 300 originalsource references.This report documents the development of this data set, its contents, and its availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which were collected using a wide range of methodologies and assumptions that may not allow comparisons among sites.

  6. A theory of ventilation estimate over hypothetical urban areas.

    PubMed

    Liu, Chun-Ho; Ng, Chi-To; Wong, Colman C C

    2015-10-15

    Urban roughness is a major factor governing the flows and scalar transport in the atmospheric boundary layer (ABL) but our understanding is rather limited. The ventilation and pollutant removal of hypothetical urban areas consisting of various types of street canyons are examined using computational fluid dynamics (CFD). The aerodynamic resistance, ventilation efficiency, and pollutant removal are measured by the friction factor f, air exchange rate (ACH), and pollutant exchange rate (PCH), respectively. Two source configurations of passive tracer, ground-level-only (Tracer 0) and all-solid-boundary (Tracer 1) are employed to contrast their transport behavior. It is found that the ventilation and pollutant removal are largely attributed to their turbulent components (over 60%). Moreover, with a consistent support from analytical solution and CFD results, the turbulent ACH is a linear function of the square root of the friction factor (ACH'∝f(1/2)) regardless of building geometry. Tracer 0 and Tracer 1 exhibit diversified removal behavior as functions of friction factor so analytical parameterizations have not yet been developed. In view of the large portion of aged air removal by turbulence, it is proposed that the aerodynamic resistance can serve as an estimate to the minimum ventilation efficiency of urban areas. PMID:25901939

  7. A theory of ventilation estimate over hypothetical urban areas.

    PubMed

    Liu, Chun-Ho; Ng, Chi-To; Wong, Colman C C

    2015-10-15

    Urban roughness is a major factor governing the flows and scalar transport in the atmospheric boundary layer (ABL) but our understanding is rather limited. The ventilation and pollutant removal of hypothetical urban areas consisting of various types of street canyons are examined using computational fluid dynamics (CFD). The aerodynamic resistance, ventilation efficiency, and pollutant removal are measured by the friction factor f, air exchange rate (ACH), and pollutant exchange rate (PCH), respectively. Two source configurations of passive tracer, ground-level-only (Tracer 0) and all-solid-boundary (Tracer 1) are employed to contrast their transport behavior. It is found that the ventilation and pollutant removal are largely attributed to their turbulent components (over 60%). Moreover, with a consistent support from analytical solution and CFD results, the turbulent ACH is a linear function of the square root of the friction factor (ACH'∝f(1/2)) regardless of building geometry. Tracer 0 and Tracer 1 exhibit diversified removal behavior as functions of friction factor so analytical parameterizations have not yet been developed. In view of the large portion of aged air removal by turbulence, it is proposed that the aerodynamic resistance can serve as an estimate to the minimum ventilation efficiency of urban areas.

  8. Optimal Estimation of Phenological Crop Model Parameters for Rice (Oryza sativa)

    NASA Astrophysics Data System (ADS)

    Sharifi, H.; Hijmans, R. J.; Espe, M.; Hill, J. E.; Linquist, B.

    2015-12-01

    Crop phenology models are important components of crop growth models. In the case of phenology models, generally only a few parameters are calibrated and default cardinal temperatures are used which can lead to a temperature-dependent systematic phenology prediction error. Our objective was to evaluate different optimization approaches in the Oryza2000 and CERES-Rice phenology sub-models to assess the importance of optimizing cardinal temperatures on model performance and systematic error. We used two optimization approaches: the typical single-stage (planting to heading) and three-stage model optimization (for planting to panicle initiation (PI), PI to heading (HD), and HD to physiological maturity (MT)) to simultaneously optimize all model parameters. Data for this study was collected over three years and six locations on seven California rice cultivars. A temperature-dependent systematic error was found for all cultivars and stages, however it was generally small (systematic error < 2.2). Both optimization approaches in both models resulted in only small changes in cardinal temperature relative to the default values and thus optimization of cardinal temperatures did not affect systematic error or model performance. Compared to single stage optimization, three-stage optimization had little effect on determining time to PI or HD but significantly improved the precision in determining the time from HD to MT: the RMSE reduced from an average of 6 to 3.3 in Oryza2000 and from 6.6 to 3.8 in CERES-Rice. With regards to systematic error, we found a trade-off between RMSE and systematic error when optimization objective set to minimize RMSE or systematic error. Therefore, it is important to find the limits within which the trade-offs between RMSE and systematic error are acceptable, especially in climate change studies where this can prevent erroneous conclusions.

  9. Biosolids, crop, and groundwater data for a biosolids-application area near Deer Trail, Colorado, 2009 and 2010

    USGS Publications Warehouse

    Yager, Tracy J.B.; Smith, David B.; Crock, James G.

    2012-01-01

    During 2009 and 2010, the U.S. Geological Survey monitored the chemical composition of biosolids, crops, and groundwater related to biosolids applications near Deer Trail, Colorado, in cooperation with the Metro Wastewater Reclamation District. This monitoring effort was a continuation of the monitoring program begun in 1999 in cooperation with the Metro Wastewater Reclamation District and the North Kiowa Bijou Groundwater Management District. The monitoring program addressed concerns from the public about potential chemical effects from applications of biosolids to farmland in the area near Deer Trail, Colo. This report presents chemical data from 2009 and 2010 for biosolids, crops, and alluvial and bedrock groundwater. The chemical data include the constituents of highest concern to the public (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, zinc, and plutonium) in addition to many other constituents. The groundwater section also includes data for precipitation, air temperature, and depth to groundwater at various groundwater-monitoring sites.

  10. Biosolids, crop, and groundwater data for a biosolids-application area near Deer Trail, Colorado, 2007 and 2008

    USGS Publications Warehouse

    Yager, Tracy J.B.; Smith, David B.; Crock, James G.

    2011-01-01

    During 2007 and 2008, the U.S. Geological Survey monitored the chemical composition of biosolids, crops, and groundwater related to biosolids applications near Deer Trail, Colorado, in cooperation with the Metro Wastewater Reclamation District. This monitoring effort was a continuation of the monitoring program begun in 1999 in cooperation with the Metro Wastewater Reclamation District and the North Kiowa Bijou Groundwater Management District. The monitoring program addressed concerns from the public about potential chemical effects from applications of biosolids to farmland in the area near Deer Trail, Colo. This report presents chemical data from 2007 and 2008 for biosolids, crops, and alluvial and bedrock groundwater. The chemical data include the constituents of highest concern to the public (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, zinc, and plutonium) in addition to many other constituents. The groundwater section also includes data for precipitation, air temperature, and depth to groundwater at various groundwater-monitoring sites.

  11. Biosolids, Crop, and Ground-Water Data for a Biosolids-Application Area Near Deer Trail, Colorado, 2004 Through 2006

    USGS Publications Warehouse

    Yager, Tracy J.B.; Smith, David B.; Crock, James G.

    2009-01-01

    From 2004 through 2006, the U.S. Geological Survey monitored the chemical composition of biosolids, crops, dust, and ground water related to biosolids applications near Deer Trail, Colorado, in cooperation with the Metro Wastewater Reclamation District. This monitoring effort was a continuation of the monitoring program begun in 1999 in cooperation with the Metro Wastewater Reclamation District and the North Kiowa Bijou Groundwater Management District. The monitoring program addresses concerns from the public about the chemical effects from applications of biosolids to farmland in the Deer Trail, Colorado, area. This report presents chemical data from 2004 through 2006 for biosolids, crops, and alluvial and bedrock ground water. The chemical data include the constituents of highest concern to the public (arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, zinc, and plutonium) in addition to many other constituents. The ground-water section also includes climate and water-level data.

  12. Bowen ratio/energy balance technique for estimating crop net CO2 assimilation, and comparison with a canopy chamber

    NASA Astrophysics Data System (ADS)

    Held, A. A.; Steduto, P.; Orgaz, F.; Matista, A.; Hsiao, T. C.

    1990-12-01

    This paper describes a Bowen ratio/energy balance (BREB) system which, in conjunction with an infra-red gas analyzer (IRGA), is referred to as BREB+ and is used to estimate evapotranspiration ( ET) and net CO2 flux ( NCF) over crop canopies. The system is composed of a net radiometer, soil heat flux plates, two psychrometers based on platinum resistance thermometers (PRT), bridge circuits to measure resistances, an IRGA, air pumps and switching valves, and a data logger. The psychrometers are triple shielded and aspirated, and with aspiration also between the two inner shields. High resistance (1 000 ohm) PRT's are used for dry and wet bulbs to minimize errors due to wiring and connector resistances. A high (55 K ohm) fixed resistance serves as one arm of the resistance bridge to ensure linearity in output signals. To minimize gaps in data, to allow measurements at short (e.g., 5 min) intervals, and to simplify operation, the psychrometers were fixed at their upper and lower position over the crop and not alternated. Instead, the PRT's, connected to the bridge circuit and the data logger, were carefully calibrated together. Field tests using a common air source showed appartent effects of the local environment around each psychrometer on the temperatures measured. ET rates estimated with the BREB system were compared to those measured with large lysimeters. Daily totals agreed within 5%. There was a tendency, however, for the lysimeter measurements to lag behind the BREB measurements. Daily patterns of NCF estimated with the BREB+ system are consistent with expectations from theories and data in the literature. Side-by-side comparisons with a stirred Mylar canopy chamber showed similar NCF patterns. On the other hand, discrepancies between the results of the two methods were quite marked in the morning or afternoon on certain dates. Part of the discrepancies may be attributed to inaccuracies in the psychrometric temperature measurements. Other possible causes

  13. Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

    NASA Technical Reports Server (NTRS)

    Zhang, Qingyuan; Cheng, Yen-Ben; Lyapustin, Alexei I.; Wang, Yujie; Xiao, Xiangming; Suyker, Andrew; Verma, Shashi; Tan, Bin; Middleton, Elizabeth M.

    2014-01-01

    Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) = 35? to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA = 35?. The fourth experiment included only backscatter observations with VZA = 35?. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation

  14. Establishing Crop Productivity Using RADARSAT-2

    NASA Astrophysics Data System (ADS)

    McNairn, H.; Shang, J.; Jiao, X.; Deschamps, B.

    2012-07-01

    Crop productivity is influenced by a number of management and environmental conditions, and variations in crop growth can occur in-season due to, for example, unfavourable meteorological conditions. Consequently information on crop growth must be temporally frequent in order to adequately characterize crop productivity. Leaf Area Index (LAI) is a key indicator of crop productivity and a number of methods have been developed to derive LAI from optical satellite data. Integration of LAI estimates from synthetic aperture radar (SAR) sensors would assist in efforts to monitor crop production through the growing season, particularly during periods of persistent cloud cover. Consequently, Agriculture and Agri-Food Canada has assessed the capability of RADARSAT-2 data to estimate LAI. The results of a sensitivity analysis revealed that several SAR polarimetric variables were strongly correlated with LAI derived from optical sensors for small grain crops. As the growing season progressed, contributions from volume scattering from the crop canopies increased. This led to the sensitivity of the intensity of linear cross-polarization backscatter, entropy and the Freeman-Durden volume scattering component, to LAI. For wheat and oats, correlations above 0.8 were reported. Following this sensitivity analysis, the Water Cloud Model (WCM) was parameterized using LAI, soil moisture and SAR data. A look up table inversion approach to estimate LAI from SAR parameters, using the WCM, was subsequently developed. This inversion approach can be used to derive LAI from sensors like RADARSAT-2 to support the monitoring of crop condition throughout the cropping season.

  15. Use of UAS remote sensing data to estimate crop ET at high spatial resolution

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. However, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the spatial resolution to capture...

  16. Estimating hourly crop ET using a two-source energy balance model and multispectral airborne imagery

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Efficient water use through improved irrigation scheduling is expected to moderate fast declining groundwater levels and improve sustainability of the Ogallala Aquifer. Thus, an accurate estimation of spatial actual evapotranspiration (ET) is needed for this purpose. Therefore, during 2007, the Bush...

  17. A comparison of operational remote sensing-based models for estimating crop evapotranspiration

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The integration of remotely sensed data into models of actual evapotranspiration has allowed for the estimation of water consumption across agricultural regions. Two modeling approaches have been successfully applied. The first approach computes a surface energy balance using the radiometric surface...

  18. Accuracy in the estimation of quantitative minimal area from the diversity/area curve.

    PubMed

    Vives, Sergi; Salicrú, Miquel

    2005-05-01

    The problem of representativity is fundamental in ecological studies. A qualitative minimal area that gives a good representation of species pool [C.M. Bouderesque, Methodes d'etude qualitative et quantitative du benthos (en particulier du phytobenthos), Tethys 3(1) (1971) 79] can be discerned from a quantitative minimal area which reflects the structural complexity of community [F.X. Niell, Sobre la biologia de Ascophyllum nosodum (L.) Le Jolis en Galicia, Invest. Pesq. 43 (1979) 501]. This suggests that the populational diversity can be considered as the value of the horizontal asymptote corresponding to the curve sample diversity/biomass [F.X. Niell, Les applications de l'index de Shannon a l'etude de la vegetation interdidale, Soc. Phycol. Fr. Bull. 19 (1974) 238]. In this study we develop a expression to determine minimal areas and use it to obtain certain information about the community structure based on diversity/area curve graphs. This expression is based on the functional relationship between the expected value of the diversity and the sample size used to estimate it. In order to establish the quality of the estimation process, we obtained the confidence intervals as a particularization of the functional (h-phi)-entropies proposed in [M. Salicru, M.L. Menendez, D. Morales, L. Pardo, Asymptotic distribution of (h,phi)-entropies, Commun. Stat. (Theory Methods) 22 (7) (1993) 2015]. As an example used to demonstrate the possibilities of this method, and only for illustrative purposes, data about a study on the rocky intertidal seawed populations in the Ria of Vigo (N.W. Spain) are analyzed [F.X. Niell, Estudios sobre la estructura, dinamica y produccion del Fitobentos intermareal (Facies rocosa) de la Ria de Vigo. Ph.D. Mem. University of Barcelona, Barcelona, 1979]. PMID:15893337

  19. Accuracy in the estimation of quantitative minimal area from the diversity/area curve.

    PubMed

    Vives, Sergi; Salicrú, Miquel

    2005-05-01

    The problem of representativity is fundamental in ecological studies. A qualitative minimal area that gives a good representation of species pool [C.M. Bouderesque, Methodes d'etude qualitative et quantitative du benthos (en particulier du phytobenthos), Tethys 3(1) (1971) 79] can be discerned from a quantitative minimal area which reflects the structural complexity of community [F.X. Niell, Sobre la biologia de Ascophyllum nosodum (L.) Le Jolis en Galicia, Invest. Pesq. 43 (1979) 501]. This suggests that the populational diversity can be considered as the value of the horizontal asymptote corresponding to the curve sample diversity/biomass [F.X. Niell, Les applications de l'index de Shannon a l'etude de la vegetation interdidale, Soc. Phycol. Fr. Bull. 19 (1974) 238]. In this study we develop a expression to determine minimal areas and use it to obtain certain information about the community structure based on diversity/area curve graphs. This expression is based on the functional relationship between the expected value of the diversity and the sample size used to estimate it. In order to establish the quality of the estimation process, we obtained the confidence intervals as a particularization of the functional (h-phi)-entropies proposed in [M. Salicru, M.L. Menendez, D. Morales, L. Pardo, Asymptotic distribution of (h,phi)-entropies, Commun. Stat. (Theory Methods) 22 (7) (1993) 2015]. As an example used to demonstrate the possibilities of this method, and only for illustrative purposes, data about a study on the rocky intertidal seawed populations in the Ria of Vigo (N.W. Spain) are analyzed [F.X. Niell, Estudios sobre la estructura, dinamica y produccion del Fitobentos intermareal (Facies rocosa) de la Ria de Vigo. Ph.D. Mem. University of Barcelona, Barcelona, 1979].

  20. Evapotranspiration measurement and crop coefficient estimation over a spring wheat Farmland ecosystem in the Loess Plateau.

    PubMed

    Yang, Fulin; Zhang, Qiang; Wang, Runyuan; Zhou, Jing

    2014-01-01

    Evapotranspiration (ET) is an important component of the surface energy balance and hydrological cycle. In this study, the eddy covariance technique was used to measure ET of the semi-arid farmland ecosystem in the Loess Plateau during 2010 growing season (April to September). The characteristics and environmental regulations of ET and crop coefficient (Kc) were investigated. The results showed that the diurnal variation of latent heat flux (LE) was similar to single-peak shape for each month, with the largest peak value of LE occurring in August (151.4 W m(-2)). The daily ET rate of the semi-arid farmland in the Loess Plateau also showed clear seasonal variation, with the maximum daily ET rate of 4.69 mm day(-1). Cumulative ET during 2010 growing season was 252.4 mm, and lower than precipitation. Radiation was the main driver of farmland ET in the Loess Plateau, which explained 88% of the variances in daily ET (p<0.001). The farmland Kc values showed the obvious seasonal fluctuation, with the average of 0.46. The correlation analysis between daily Kc and its major environmental factors indicated that wind speed (Ws), relative humidity (RH), soil water content (SWC), and atmospheric vapor pressure deficit (VPD) were the major environmental regulations of daily Kc. The regression analysis results showed that Kc exponentially decreased with Ws increase, an exponentially increased with RH, SWC increase, and a linearly decreased with VPD increase. An experiential Kc model for the semi-arid farmland in the Loess Plateau, driven by Ws, RH, SWC and VPD, was developed, showing a good consistency between the simulated and the measured Kc values. PMID:24941017

  1. Evapotranspiration Measurement and Crop Coefficient Estimation over a Spring Wheat Farmland Ecosystem in the Loess Plateau

    PubMed Central

    Yang, Fulin; Zhang, Qiang; Wang, Runyuan; Zhou, Jing

    2014-01-01

    Evapotranspiration (ET) is an important component of the surface energy balance and hydrological cycle. In this study, the eddy covariance technique was used to measure ET of the semi-arid farmland ecosystem in the Loess Plateau during 2010 growing season (April to September). The characteristics and environmental regulations of ET and crop coefficient (Kc) were investigated. The results showed that the diurnal variation of latent heat flux (LE) was similar to single-peak shape for each month, with the largest peak value of LE occurring in August (151.4 W m−2). The daily ET rate of the semi-arid farmland in the Loess Plateau also showed clear seasonal variation, with the maximum daily ET rate of 4.69 mm day−1. Cumulative ET during 2010 growing season was 252.4 mm, and lower than precipitation. Radiation was the main driver of farmland ET in the Loess Plateau, which explained 88% of the variances in daily ET (p<0.001). The farmland Kc values showed the obvious seasonal fluctuation, with the average of 0.46. The correlation analysis between daily Kc and its major environmental factors indicated that wind speed (Ws), relative humidity (RH), soil water content (SWC), and atmospheric vapor pressure deficit (VPD) were the major environmental regulations of daily Kc. The regression analysis results showed that Kc exponentially decreased with Ws increase, an exponentially increased with RH, SWC increase, and a linearly decreased with VPD increase. An experiential Kc model for the semi-arid farmland in the Loess Plateau, driven by Ws, RH, SWC and VPD, was developed, showing a good consistency between the simulated and the measured Kc values. PMID:24941017

  2. Evapotranspiration measurement and crop coefficient estimation over a spring wheat Farmland ecosystem in the Loess Plateau.

    PubMed

    Yang, Fulin; Zhang, Qiang; Wang, Runyuan; Zhou, Jing

    2014-01-01

    Evapotranspiration (ET) is an important component of the surface energy balance and hydrological cycle. In this study, the eddy covariance technique was used to measure ET of the semi-arid farmland ecosystem in the Loess Plateau during 2010 growing season (April to September). The characteristics and environmental regulations of ET and crop coefficient (Kc) were investigated. The results showed that the diurnal variation of latent heat flux (LE) was similar to single-peak shape for each month, with the largest peak value of LE occurring in August (151.4 W m(-2)). The daily ET rate of the semi-arid farmland in the Loess Plateau also showed clear seasonal variation, with the maximum daily ET rate of 4.69 mm day(-1). Cumulative ET during 2010 growing season was 252.4 mm, and lower than precipitation. Radiation was the main driver of farmland ET in the Loess Plateau, which explained 88% of the variances in daily ET (p<0.001). The farmland Kc values showed the obvious seasonal fluctuation, with the average of 0.46. The correlation analysis between daily Kc and its major environmental factors indicated that wind speed (Ws), relative humidity (RH), soil water content (SWC), and atmospheric vapor pressure deficit (VPD) were the major environmental regulations of daily Kc. The regression analysis results showed that Kc exponentially decreased with Ws increase, an exponentially increased with RH, SWC increase, and a linearly decreased with VPD increase. An experiential Kc model for the semi-arid farmland in the Loess Plateau, driven by Ws, RH, SWC and VPD, was developed, showing a good consistency between the simulated and the measured Kc values.

  3. Crop changes from the XVI century to the present in a hill/mountain area of eastern Liguria (Italy)

    PubMed Central

    Gentili, Rodolfo; Gentili, Elio; Sgorbati, Sergio

    2009-01-01

    Background Chronological information on the composition and structure of agrocenoses and detailed features of land cover referring to specific areas are uncommon in ethnobotanical studies, especially for periods before the XIX century. The aim of this study was to analyse the type of crop or the characteristics of soil cover from the XVI century to the present. Methods This diachronic analysis was accomplished through archival research on the inventories of the Parish of St. Mary and those of the Municipality of Pignone and from recent surveys conducted in an area of eastern Liguria (Italy). Results Archival data revealed that in study area the primary means of subsistence during the last five centuries, until the first half of the XX century, was chestnuts. In the XVIII and XIX centuries, crop diversification strongly increased in comparison with previous and subsequent periods. In more recent times, the abandonment of agricultural practices has favoured the re-colonisation of mixed woodland or cluster-pine woodland. Conclusion Ancient documents in the ecclesiastic or municipal inventories can be a very useful tool for enhancing the knowledge of agricultural practice, as well as of subsistence methods favoured by local populations during a particular time and for reconstructing land use change over time. PMID:19361339

  4. Estimating time and spatial distribution of snow water equivalent in the Hakusan area

    NASA Astrophysics Data System (ADS)

    Tanaka, K.; Matsui, Y.; Touge, Y.

    2015-12-01

    In the Sousei program, on-going Japanese research program for risk information on climate change, assessing the impact of climate change on water resources is attempted using the integrated water resources model which consists of land surface model, irrigation model, river routing model, reservoir operation model, and crop growth model. Due to climate change, reduction of snowfall amount, reduction of snow cover and change in snowmelt timing, change in river discharge are of increasing concern. So, the evaluation of snow water amount is crucial for assessing the impact of climate change on water resources in Japan. To validate the snow simulation of the land surface model, time and spatial distribution of the snow water equivalent was estimated using the observed surface meteorological data and RAP (Radar Analysis Precipitation) data. Target area is Hakusan. Hakusan means 'white mountain' in Japanese. Water balance of the Tedori River Dam catchment was checked with daily inflow data. Analyzed runoff was generally well for the period from 2010 to 2012. From the result for 2010-2011 winter, maximum snow water equivalent in the headwater area of the Tedori River dam reached more than 2000mm in early April. On the other hand, due to the underestimation of RAP data, analyzed runoff was under estimated from 2006 to 2009. This underestimation is probably not from the lack of land surface model, but from the quality of input precipitation data. In the original RAP, only the rain gauge data of JMA (Japan Meteorological Agency) were used in the analysis. Recently, other rain gauge data of MLIT (Ministry of Land, Infrastructure, Transport and Tourism) and local government have been added in the analysis. So, the quality of the RAP data especially in the mountain region has been greatly improved. "Reanalysis" of the RAP precipitation is strongly recommended using all the available off-line rain gauges information. High quality precipitation data will contribute to validate

  5. Estimates of spatial and temporal variation of energy crops biomass yields in the US

    NASA Astrophysics Data System (ADS)

    Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

    2013-12-01

    Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors

  6. A comparison of measured and estimated meteorological data for use in crop growth modeling

    NASA Technical Reports Server (NTRS)

    Perry, C. R., Jr.; Rogers, J. L.; Ritchie, J. T.

    1982-01-01

    Gridded spatial estimates of maximum temperature, minimum temperature, precipitation, and solar radiation, prepared for agricultural use from World Meteorological Organization surface reports and enhanced by polar orbiting satellites were compared with daily meteorological data measured at various agricultural research facilities across the United States to determine their level of accuracy. Preliminary results indicate that daily maximum temperature can be determined to within 9.1 degrees Celsius with ninety percent confidence. With similar levels of confidence, daily minimum temperature can be determined to within 6.7 degrees Celsius, daily solar radiation to within 231.2 cal/sq cm min, and daily precipitation to within 9.7 millimeters.

  7. Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea.

    PubMed

    Kim, Youngsun; Seo, Youngho; Kraus, David; Klatt, Steffen; Haas, Edwin; Tenhunen, John; Kiese, Ralf

    2015-10-01

    Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents. PMID:26005748

  8. Estimation and mitigation of N2O emission and nitrate leaching from intensive crop cultivation in the Haean catchment, South Korea.

    PubMed

    Kim, Youngsun; Seo, Youngho; Kraus, David; Klatt, Steffen; Haas, Edwin; Tenhunen, John; Kiese, Ralf

    2015-10-01

    Considering intensive agricultural management practices and environmental conditions, the LandscapeDNDC model was applied for simulation of yields, N2O emission and nitrate leaching from major upland crops and temperate deciduous forest of the Haean catchment, South Korea. Fertilization rates were high (up to 314 kg N ha(-1) year(-1)) and resulted in simulated direct N2O emissions from potato, radish, soybean and cabbage fields of 1.9 and 2.1 kg N ha(-1) year(-1) in 2009 and 2010, respectively. Nitrate leaching was identified as the dominant pathway of N losses in the Haean catchment with mean annual rates of 112.2 and 125.4 kg N ha(-1) year(-1), causing threats to water quality and leading to substantial indirect N2O emissions of 0.84 and 0.94 kg N ha(-1) year(-1) in 2009 and 2010 as estimates by applying the IPCC EF5. Simulated N2O emissions from temperate deciduous forest were low (approx. 0.50 kg N ha(-1) year(-1)) and predicted nitrate leaching rates were even negligible (≤0.01 kg N ha(-1) year(-1)). On catchment scale more than 50% of the total N2O emissions and up to 75% of nitrate leaching originated from fertilized upland fields, only covering 24% of the catchment area. Taking into account area coverage of simulated upland crops and other land uses these numbers agree well with nitrate loads calculated from discharge and concentration measurements at the catchment outlet. The change of current agricultural management practices showed a high potential of reducing N2O emission and nitrate leaching while maintaining current crop yields. Reducing (39%) and splitting N fertilizer application into 3 times was most effective and lead to about 54% and 77% reducing of N2O emission and nitrate leaching from the Haean catchment, the latter potentially contributing to improved water quality in the Soyang River Dam, which is the major source of drinking water for metropolitan residents.

  9. Large Area Crop Inventory Experiment (LACIE). An early estimate of small grains acreage

    NASA Technical Reports Server (NTRS)

    Lea, R. N.; Kern, D. M. (Principal Investigator)

    1979-01-01

    The author has identified the following significant results. A major advantage of this scheme is that it needs minimal human intervention. The entire scheme, with the exception of the choice of dates, can be computerized and the results obtained in minutes. The decision to limit the number of acquisitions processed to four was made to facilitate operation on the particular computer being used. Some earlier runs on another computer system were based on as many as seven biophase-1 acquisitions.

  10. Estimating regional wheat yield from the shape of decreasing curves of green area index temporal profiles retrieved from MODIS data

    NASA Astrophysics Data System (ADS)

    Kouadio, Louis; Duveiller, Grégory; Djaby, Bakary; El Jarroudi, Moussa; Defourny, Pierre; Tychon, Bernard

    2012-08-01

    Earth observation data, owing to their synoptic, timely and repetitive coverage, have been recognized as a valuable tool for crop monitoring at different levels. At the field level, the close correlation between green leaf area (GLA) during maturation and grain yield in wheat revealed that the onset and rate of senescence appeared to be important factors for determining wheat grain yield. Our study sought to explore a simple approach for wheat yield forecasting at the regional level, based on metrics derived from the senescence phase of the green area index (GAI) retrieved from remote sensing data. This study took advantage of recent methodological improvements in which imagery with high revisit frequency but coarse spatial resolution can be exploited to derive crop-specific GAI time series by selecting pixels whose ground-projected instantaneous field of view is dominated by the target crop: winter wheat. A logistic function was used to characterize the GAI senescence phase and derive the metrics of this phase. Four regression-based models involving these metrics (i.e., the maximum GAI value, the senescence rate and the thermal time taken to reach 50% of the green surface in the senescent phase) were related to official wheat yield data. The performances of such models at this regional scale showed that final yield could be estimated with an RMSE of 0.57 ton ha-1, representing about 7% as relative RMSE. Such an approach may be considered as a first yield estimate that could be performed in order to provide better integrated yield assessments in operational systems.

  11. How healthy is urban horticulture in high traffic areas? Trace metal concentrations in vegetable crops from plantings within inner city neighbourhoods in Berlin, Germany.

    PubMed

    Säumel, Ina; Kotsyuk, Iryna; Hölscher, Marie; Lenkereit, Claudia; Weber, Frauke; Kowarik, Ingo

    2012-06-01

    Food production by urban dwellers is of growing importance in developing and developed countries. Urban horticulture is associated with health risks as crops in urban settings are generally exposed to higher levels of pollutants than those in rural areas. We determined the concentration of trace metals in the biomass of different horticultural crops grown in the inner city of Berlin, Germany, and analysed how the local setting shaped the concentration patterns. We revealed significant differences in trace metal concentrations depending on local traffic, crop species, planting style and building structures, but not on vegetable type. Higher overall traffic burden increased trace metal content in the biomass. The presence of buildings and large masses of vegetation as barriers between crops and roads reduced trace metal content in the biomass. Based on this we discuss consequences for urban horticulture, risk assessment, and planting and monitoring guidelines for cultivation and consumption of crops.

  12. A simulation study of Large Area Crop Inventory Experiment (LACIE) technology

    NASA Technical Reports Server (NTRS)

    Ziegler, L. (Principal Investigator); Potter, J.

    1979-01-01

    The author has identified the following significant results. The LACIE performance predictor (LPP) was used to replicate LACIE phase 2 for a 15 year period, using accuracy assessment results for phase 2 error components. Results indicated that the (LPP) simulated the LACIE phase 2 procedures reasonably well. For the 15 year simulation, only 7 of the 15 production estimates were within 10 percent of the true production. The simulations indicated that the acreage estimator, based on CAMS phase 2 procedures, has a negative bias. This bias was too large to support the 90/90 criterion with the CV observed and simulated for the phase 2 production estimator. Results of this simulation study validate the theory that the acreage variance estimator in LACIE was conservative.

  13. Large Area Crop Inventory Experiment (LACIE). The boundary pixel study in Kansas and North Dakota

    NASA Technical Reports Server (NTRS)

    Register, D. T. (Principal Investigator); Ona, A. L.

    1979-01-01

    The author has identified the following significant results. The statistical mapping approach to handling boundary pixels can be used as a standard for objectively comparing the cluster based technique, the maximum likelihood estimate based technique, and multicategory labeling.

  14. Improving root-zone soil moisture estimations using dynamic root growth and crop phenology

    NASA Astrophysics Data System (ADS)

    Hashemian, Minoo; Ryu, Dongryeol; Crow, Wade T.; Kustas, William P.

    2015-12-01

    Water Energy Balance (WEB) Soil Vegetation Atmosphere Transfer (SVAT) modelling can be used to estimate soil moisture by forcing the model with observed data such as precipitation and solar radiation. Recently, an innovative approach that assimilates remotely sensed thermal infrared (TIR) observations into WEB-SVAT to improve the results has been proposed. However, the efficacy of the model-observation integration relies on the model's realistic representation of soil water processes. Here, we explore methods to improve the soil water processes of a simple WEB-SVAT model by adopting and incorporating an exponential root water uptake model with water stress compensation and establishing a more appropriate soil-biophysical linkage between root-zone moisture content, above-ground states and biophysical indices. The existing WEB-SVAT model is extended to a new Multi-layer WEB-SVAT with Dynamic Root distribution (MWSDR) that has five soil layers. Impacts of plant root depth variations, growth stages and phenological cycle of the vegetation on transpiration are considered in developing stages. Hydrometeorological and biogeophysical measurements collected from two experimental sites, one in Dookie, Victoria, Australia and the other in Ponca, Oklahoma, USA, are used to validate the new model. Results demonstrate that MWSDR provides improved soil moisture, transpiration and evaporation predictions which, in turn, can provide an improved physical basis for assimilating remotely sensed data into the model. Results also show the importance of having an adequate representation of vegetation-related transpiration process for an appropriate simulation of water transfer in a complicated system of soil, plants and atmosphere.

  15. [Soil and water loss from cultivated slope land derived from granite under different cropping systems in Three-Gorges reservoir areas].

    PubMed

    Xiang, W; Liang, C; Li, W

    2001-02-01

    The water and soil loss caused by cultivation on slope land derived from granite under different cropping systems in the Three-Gorges reservoir area was analyzed based on the data from localized observation. The results showed that in this area, proximately 60% of total annual rainfall, distributed in May to August, and 60% of soil erosion occurred in these four months, with 50% in June and July. The coverage rates under different cropping systems differed significantly, e.g., triple-cropping systems and inter-croping system with perennial plants (grass and day lily) had a bigger covering than double-cropping systems. The soil loss under cropping system with peanut was much lower than that with sweet potato, because the covering rate of the former was higher than that of the latter in summer raining season. The sequence of soil and nutrient loss for different cropping systems was rape (wheat) sweet potato > rape(wheat)/corn/sweet potato > rape(wheat)/corn/peanut/rape(wheat)/grass/peanut/rape(wheat)/day lily/peanut. It was concluded that soil loss from cultivated slope land could be controlled below a permissible value, if rational cropping and management systems were adopted.

  16. Adoption of an unmanned helicopter for low-altitude remote sensing to estimate yield and total biomass of a rice crop

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A radio-controlled unmanned helicopter-based LARS (Low-Altitude Remote Sensing) platform was used to acquire quality images of high spatial and temporal resolution, in order to estimate yield and total biomass of a rice crop (Oriza Sativa, L.). Fifteen rice field plots with five N-treatments (0, 33,...

  17. Analysis of scanner data for crop inventories

    NASA Technical Reports Server (NTRS)

    Horvath, R. (Principal Investigator); Cicone, R. C.; Kauth, R. J.; Malila, W. A.; Pont, W.; Thelen, B.; Sellman, A.

    1981-01-01

    Accomplishments for a machine-oriented small grains labeler T&E, and for Argentina ground data collection are reported. Features of the small grains labeler include temporal-spectral profiles, which characterize continuous patterns of crop spectral development, and crop calendar shift estimation, which adjusts for planting date differences of fields within a crop type. Corn and soybean classification technology development for area estimation for foreign commodity production forecasting is reported. Presentations supporting quarterly project management reviews and a quarterly technical interchange meeting are also included.

  18. Density and Distribution of Xylocopa Nests (Hymenoptera: Apidae) in Caatinga Areas in the Surroundings of Passion Fruit Crops.

    PubMed

    Martins, C F; de Siqueira, K M M; Kiill, L H P; Sá, I I S; Aguiar, C M L

    2014-08-01

    Due to their importance as pollinators of many plant species, this study aimed to know the nest density, spatial distribution, and nesting substrates used by Xylocopa species in the Caatinga, a xerophilous vegetation of Northeastern Brazil. Three areas of Caatinga in the surroundings of passion fruit crops were sampled. The bee species found in these areas were Xylocopa grisescens Lepeletier and Xylocopa frontalis (Olivier). All nests were in Commiphora leptophloeos (Burseraceae) trees (n = 113). Phytosociological analysis showed that this tree species presented the highest absolute density (212.5 individuals/ha) and index of importance value (52.7). The distribution pattern of the C. leptophloeos was aggregated. The nests were located in dead and dried branches with an average diameter of 5.3 ± 2.0 cm (n = 43). The mean number of nests/tree was 3.1 ± 2.8 (n = 113). The less disturbed area showed 6.7 nests/ha and 4.2 nests/tree. In the disturbed areas, 0.9 nests/ha and 2.4 to 2.7 nests/tree were observed. The availability of substrate for nesting in the studied areas and its importance as a limiting factor for nesting are discussed.

  19. Global crop forecasting

    NASA Technical Reports Server (NTRS)

    Macdonald, R. B.; Hall, F. G.

    1980-01-01

    The needs for and remote sensing means of global crop forecasting are discussed, and key results of the Large Area Crop Inventory Experiment (LACIE) are presented. Current crop production estimates provided by foreign countries are shown often to be inadequate, and the basic elements of crop production forecasts are reviewed. The LACIE project is introduced as a proof-of-concept experiment designed to assimilate remote sensing technology, monitor global wheat production, evaluate key technical problems, modify the technique accordingly and demonstrate the feasibility of a global agricultural monitoring system. The global meteorological data, sampling and aggregation techniques, Landsat data analysis procedures and yield forecast procedures used in the experiment are outlined. Accuracy assessment procedures employed to evaluate LACIE technology performance are presented, and improvements in system efficiency and capacity during the three years of operation are pointed out. Results of LACIE estimates of Soviet, U.S. and Canadian wheat production are presented which demonstrate the feasibility and accuracy of the remote-sensing approach for global food and fiber monitoring.

  20. Integrating USDA Crop Progress Data, and Remote Sensing Evapotranspiration and Leaf Area Index in Parsimonious Modeling of Hydrologic Responses in Midwestern Landscapes

    NASA Astrophysics Data System (ADS)

    Ding, D.; Basu, N. B.; Linderman, M.

    2012-12-01

    A parsimonious hydrologic model, the Threshold-Exeedance-Lagrangian Model (TELM), was developed for the intensively managed watersheds in the agricultural Midwest. Crop vegetative progress was identified as a critical model input to the TELM due to its influence on evapotranspiration (ET) and land surface water budget. Crop phenology estimated using USDA crop progress data as well as RS-derived LAI data were compared as a function of spatial and temporal scales. We examined the hypotheses that 1) the integration of RS LAI with TELM enhances its ability to predict stream flow; 2) the enhancement of model predictions with RS-TELM depends on the spatial and temporal variability of LAI over the watershed. First, we developed methodologies for integrating RS data in the TELM framework. Second, we investigated the spatio-temporal variability of crop phenology over the whole state and identified three mesoscale watersheds with distinct levels of variability. Third, we applied five strategies in running the TELM: 1) statewide theoretical LAI curve based on general information of crop growing stages; 2) district-level theoretical LAI curve derived from USDA crop progress data; 3) watershed average LAI curve lumped from RS LAI; 4) distributed LAI derived from MODIS NDVI (Normalized Difference Vegetation Index) data; and 5) distributed MODIS ET data. By examining the hydrographs of watershed outlet streamflow, and the goodness-of-fit measures of model predictions, we further discussed the impacts of the spatio-temporal variability of crop phenology on model performances.

  1. [Characteristics of evapotranspiration and crop coefficient of agroecosystems in semi-arid area of Loess Plateau, Northwest China].

    PubMed

    Yang, Fu-Lin; Zhang, Qiang; Wang, Run-Yuan; Wang, Sheng; Yue, Ping; Wang, He-Ling; Zhao, Hong

    2013-05-01

    Evapotranspiration (ET) is an important component of ground surface energy balance and water balance, and closely related to water cycle. By using eddy covariance technique, this paper studied the ET characteristics of agroecosystems in the semi-arid area of Loess Plateau in growth season (from April to September), 2010, and analyzed the relationships between crop coefficient and environmental factors. During the observation period, the diurnal variation of latent heat flux (LE) in each month was similar to single-peak curve, and the peak value (151.4 W x m(-2)) occurred in August. The daytime energy partitioning manner showed a significant seasonal variation, with LE/R(n) < H/R(n) (R(n) was net radiation, and H was sensible heat flux) from April to June, and LE/R(n) > H/R(n) from July to September. The daily ET rate also showed a significant seasonal variation, with the maximum of 4.69 mm x d(-1). The wind speed (W(s)), relative humidity (RH), soil water content (theta), and atmospheric vapor pressure deficit (D) were the major factors affecting the crop coefficient K(c) which was exponentially decreased with increasing W(s), exponentially increased with increasing RH and theta, and linearly decreased with increasing D. PMID:24015535

  2. [Characteristics of evapotranspiration and crop coefficient of agroecosystems in semi-arid area of Loess Plateau, Northwest China].

    PubMed

    Yang, Fu-Lin; Zhang, Qiang; Wang, Run-Yuan; Wang, Sheng; Yue, Ping; Wang, He-Ling; Zhao, Hong

    2013-05-01

    Evapotranspiration (ET) is an important component of ground surface energy balance and water balance, and closely related to water cycle. By using eddy covariance technique, this paper studied the ET characteristics of agroecosystems in the semi-arid area of Loess Plateau in growth season (from April to September), 2010, and analyzed the relationships between crop coefficient and environmental factors. During the observation period, the diurnal variation of latent heat flux (LE) in each month was similar to single-peak curve, and the peak value (151.4 W x m(-2)) occurred in August. The daytime energy partitioning manner showed a significant seasonal variation, with LE/R(n) < H/R(n) (R(n) was net radiation, and H was sensible heat flux) from April to June, and LE/R(n) > H/R(n) from July to September. The daily ET rate also showed a significant seasonal variation, with the maximum of 4.69 mm x d(-1). The wind speed (W(s)), relative humidity (RH), soil water content (theta), and atmospheric vapor pressure deficit (D) were the major factors affecting the crop coefficient K(c) which was exponentially decreased with increasing W(s), exponentially increased with increasing RH and theta, and linearly decreased with increasing D.

  3. Methodology for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

    Cancer.gov

    The HINTS is designed to produce reliable estimates at the national and regional levels. GIS maps using HINTS data have been used to provide a visual representation of possible geographic relationships in HINTS cancer-related variables.

  4. Data Sources for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

    Cancer.gov

    The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

  5. Data Sources for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Cancer.gov

    The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

  6. Honeybee colony disorder in crop areas: the role of pesticides and viruses.

    PubMed

    Simon-Delso, Noa; San Martin, Gilles; Bruneau, Etienne; Minsart, Laure-Anne; Mouret, Coralie; Hautier, Louis

    2014-01-01

    As in many other locations in the world, honeybee colony losses and disorders have increased in Belgium. Some of the symptoms observed rest unspecific and their causes remain unknown. The present study aims to determine the role of both pesticide exposure and virus load on the appraisal of unexplained honeybee colony disorders in field conditions. From July 2011 to May 2012, 330 colonies were monitored. Honeybees, wax, beebread and honey samples were collected. Morbidity and mortality information provided by beekeepers, colony clinical visits and availability of analytical matrix were used to form 2 groups: healthy colonies and colonies with disorders (n = 29, n = 25, respectively). Disorders included: (1) dead colonies or colonies in which part of the colony appeared dead, or had disappeared; (2) weak colonies; (3) queen loss; (4) problems linked to brood and not related to any known disease. Five common viruses and 99 pesticides (41 fungicides, 39 insecticides and synergist, 14 herbicides, 5 acaricides and metabolites) were quantified in the samples.The main symptoms observed in the group with disorders are linked to brood and queens. The viruses most frequently found are Black Queen Cell Virus, Sac Brood Virus, Deformed Wing Virus. No significant difference in virus load was observed between the two groups. Three acaricides, 5 insecticides and 13 fungicides were detected in the analysed samples. A significant correlation was found between the presence of fungicide residues and honeybee colony disorders. A significant positive link could also be established between the observation of disorder and the abundance of crop surface around the beehive. According to our results, the role of fungicides as a potential stressor for honeybee colonies should be further studied, either by their direct and/or indirect impacts on bees and bee colonies.

  7. Honeybee Colony Disorder in Crop Areas: The Role of Pesticides and Viruses

    PubMed Central

    Simon-Delso, Noa; San Martin, Gilles; Bruneau, Etienne; Minsart, Laure-Anne; Mouret, Coralie; Hautier, Louis

    2014-01-01

    As in many other locations in the world, honeybee colony losses and disorders have increased in Belgium. Some of the symptoms observed rest unspecific and their causes remain unknown. The present study aims to determine the role of both pesticide exposure and virus load on the appraisal of unexplained honeybee colony disorders in field conditions. From July 2011 to May 2012, 330 colonies were monitored. Honeybees, wax, beebread and honey samples were collected. Morbidity and mortality information provided by beekeepers, colony clinical visits and availability of analytical matrix were used to form 2 groups: healthy colonies and colonies with disorders (n = 29, n = 25, respectively). Disorders included: (1) dead colonies or colonies in which part of the colony appeared dead, or had disappeared; (2) weak colonies; (3) queen loss; (4) problems linked to brood and not related to any known disease. Five common viruses and 99 pesticides (41 fungicides, 39 insecticides and synergist, 14 herbicides, 5 acaricides and metabolites) were quantified in the samples.The main symptoms observed in the group with disorders are linked to brood and queens. The viruses most frequently found are Black Queen Cell Virus, Sac Brood Virus, Deformed Wing Virus. No significant difference in virus load was observed between the two groups. Three acaricides, 5 insecticides and 13 fungicides were detected in the analysed samples. A significant correlation was found between the presence of fungicide residues and honeybee colony disorders. A significant positive link could also be established between the observation of disorder and the abundance of crop surface around the beehive. According to our results, the role of fungicides as a potential stressor for honeybee colonies should be further studied, either by their direct and/or indirect impacts on bees and bee colonies. PMID:25048715

  8. A Method to Estimate Crop Effects in Passive Microwave Soil Moisture Retrieval Above C-band

    NASA Astrophysics Data System (ADS)

    Zhang, Z.; Xu, Y.; Shi, J.

    2009-12-01

    moisture) directly to the observed Brightness Temperature. On the other hand, τ-ω model is simple in formula and are widely used in soil moisture retrieval at L- or C-band. To characterize ω and t of short vegetation above C-band, we setup a Brightness Temperature database with M-D model by a variety of parameters. Then results from M-D model were matched with those from τ-ω model at the same environmental conditions by least-square deviation, so as to retrieve ω and t of vegetation above C-band. To verify the derived effective single scattering albedo ω and transmissivity t, they were used, together with the Brightness Temperature data during SMEX02/PSR flight, in τ-ω model. The results of the equation were emissivity of soil, which were then used by a Qp model to retrieve soil moisture in the same area where PSR flight passed. The retrieved soil moisture matched the measurement very good, the rmse is 0.0458. This showed our method to retrieve ω and t are reliable.

  9. [Estimation of spur dike-affected fish habitat area].

    PubMed

    Ray-Shyan, Wu; Yan-Ru, Chen; Yi-Liang, Ge

    2012-04-01

    Based on the HEC-RAS and River 2D modes, and taking 5% change rate of weighted usable area (WUA) as the threshold to define the spur dike- affected area of target fish species Acrossocheilus paradoxus in Fazi River in Taiwan, this paper studied the affected area of the fish habitat by spur dike, and, in combining with the references about the installations of spur dikes in Taiwan in recent 10 years, analyzed the relative importance of related affecting factors such as dike height, dike length (water block rate), average slope gradient of river way, single or double spur dike, and flow discharge. In spite of the length of the dike, the affected area in downstream was farther, and was about 2-6 times as large as that in upstream. The ratio of the affected area in downstream / upstream decreased with increasing slope gradient, but increased with increasing dike length and flow discharge. When the discharge was approximate to 10 years return periods, the ratio of the affected area would be close to a constant of 2. Building double spur dike would produce a better WUA than building single spur dike.

  10. Estimated crop loss due to coconut mite and financial analysis of controlling the pest using the acaricide abamectin.

    PubMed

    Rezende, Daniela; Melo, José W S; Oliveira, José E M; Gondim, Manoel G C

    2016-07-01

    Reducing the losses caused by Aceria guerreronis Keifer has been an arduous task for farmers. However, there are no detailed studies on losses that simultaneously analyse correlated parameters, and very few studies that address the economic viability of chemical control, the main strategy for managing this pest. In this study the objectives were (1) to estimate the crop loss due to coconut mite and (2) to perform a financial analysis of acaricide application to control the pest. For this, the following parameters were evaluated: number and weight of fruits, liquid albumen volume, and market destination of plants with and without monthly abamectin spraying (three harvests). The costs involved in the chemical control of A. guerreronis were also quantified. Higher A. guerreronis incidence on plants resulted in a 60 % decrease in the mean number of fruits harvested per bunch and a 28 % decrease in liquid albumen volume. Mean fruit weight remained unaffected. The market destination of the harvested fruit was also affected by higher A. guerreronis incidence. Untreated plants, with higher A. guerreronis infestation intensity, produced a lower proportion of fruit intended for fresh market and higher proportions of non-marketable fruit and fruit intended for industrial processing. Despite the costs involved in controlling A. guerreronis, the difference between the profit from the treated site and the untreated site was 18,123.50 Brazilian Real; this value represents 69.1 % higher profit at the treated site. PMID:27059867

  11. Estimated crop loss due to coconut mite and financial analysis of controlling the pest using the acaricide abamectin.

    PubMed

    Rezende, Daniela; Melo, José W S; Oliveira, José E M; Gondim, Manoel G C

    2016-07-01

    Reducing the losses caused by Aceria guerreronis Keifer has been an arduous task for farmers. However, there are no detailed studies on losses that simultaneously analyse correlated parameters, and very few studies that address the economic viability of chemical control, the main strategy for managing this pest. In this study the objectives were (1) to estimate the crop loss due to coconut mite and (2) to perform a financial analysis of acaricide application to control the pest. For this, the following parameters were evaluated: number and weight of fruits, liquid albumen volume, and market destination of plants with and without monthly abamectin spraying (three harvests). The costs involved in the chemical control of A. guerreronis were also quantified. Higher A. guerreronis incidence on plants resulted in a 60 % decrease in the mean number of fruits harvested per bunch and a 28 % decrease in liquid albumen volume. Mean fruit weight remained unaffected. The market destination of the harvested fruit was also affected by higher A. guerreronis incidence. Untreated plants, with higher A. guerreronis infestation intensity, produced a lower proportion of fruit intended for fresh market and higher proportions of non-marketable fruit and fruit intended for industrial processing. Despite the costs involved in controlling A. guerreronis, the difference between the profit from the treated site and the untreated site was 18,123.50 Brazilian Real; this value represents 69.1 % higher profit at the treated site.

  12. Estimating relationships among water use, nitrogen uptake and biomass production in a short-rotation woody crop plantation

    NASA Astrophysics Data System (ADS)

    Ouyang, Y.

    2015-12-01

    Short-rotation woody crop has been identified as one of the best feedstocks for bioenergy production due to their fast-growth rates. However, the biomass production, nutrient uptake, and water use efficiency under adverse environmental condition are still poorly understood. In this study, a computer model was developed to undertake these issues using STELLA (Structural Thinking and Experiential Learning Laboratory with Animation) software. Two simulation scenarios were employed: one was to quantify the mechanisms of water use, nitrogen uptake and biomass production in a eucalypt plantation under the normal soil conditions, the other was to estimate the same mechanisms under the wet and dry soil conditions. In general, the rates of evaporation, transpiration, evapotranspiration (ET), and root water uptake were in the following order: ET > root uptake > leaf transpiration > soil evaporation. A profound discrepancy in water use was observed between the wet and dry soil conditions. Leaching of nitrate-N and soluble organic N depended not only on soil N content but also on rainfall rate and duration. The yield of biomass from the eucalypt was primarily regulated by water availability in a fertilized plantation.

  13. Estimating the surface area of birds: using the homing pigeon (Columba livia) as a model.

    PubMed

    Perez, Cristina R; Moye, John K; Pritsos, Chris A

    2014-05-08

    Estimation of the surface area of the avian body is valuable for thermoregulation and metabolism studies as well as for assessing exposure to oil and other surface-active organic pollutants from a spill. The use of frozen carcasses for surface area estimations prevents the ability to modify the posture of the bird. The surface area of six live homing pigeons in the fully extended flight position was estimated using a noninvasive method. An equation was derived to estimate the total surface area of a pigeon based on its body weight. A pigeon's surface area in the fully extended flight position is approximately 4 times larger than the surface area of a pigeon in the perching position. The surface area of a bird is dependent on its physical position, and, therefore, the fully extended flight position exhibits the maximum area of a bird and should be considered the true surface area of a bird.

  14. Large Area Crop Inventory Experiment (LACIE). Detection of episodic phenomena on LANDSAT imagery. [Kansas

    NASA Technical Reports Server (NTRS)

    Chesnutwood, C. M. (Principal Investigator)

    1976-01-01

    The author has identified the following significant results. Episodic phenomena such as rainfall shortly before data pass, thin translucent clouds, cloud shadows, and aircraft condensation trails and their shadows are responsible for changes in the spectral reflectivities of some surfaces. These changes are readily detected on LANDSAT full-frame imagery. Histograms of selected areas in Kansas show a distinct decrease in mean radiance values, but also, an increase in scene contrast, in areas where recent rains had occurred. Histograms from a few individual fields indicate that the mean radiance values for winter wheat followed a different trend after a rainfall than alfalfa or grasses.

  15. Evaluation of spring wheat and barley crop calender models for the 1979 crop year

    NASA Technical Reports Server (NTRS)

    Nazare, C. V.; Carnes, J. G. (Principal Investigator)

    1981-01-01

    During the Large Area Crop Inventory Experiment, spring wheat planting date and crop development stage estimates based on historical normals were improved by the use of the Feyerherm planting date and Robertson spring wheat crop calendar models. The Supporting Research Crop Calendar Project element modified the Robertson model to reduce bias at cardinal growth stages within the growing season. These models were tested in 1980 along with a state-of-the-art barley model (Williams) against a ground-truth data set from 49 calendar year 1979 segments in the U.S. Great Plains spring wheat and barley region.

  16. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    NASA Astrophysics Data System (ADS)

    Marshall, Michael; Thenkabail, Prasad

    2015-10-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5-31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3-33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the "red-edge" spectral range (700-740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400-2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for alfalfa (R2 = 0

  17. Advantage of hyperspectral EO-1 Hyperion over multispectral IKONOS, GeoEye-1, WorldView-2, Landsat ETM+, and MODIS vegetation indices in crop biomass estimation

    USGS Publications Warehouse

    Marshall, Michael T.; Thenkabail, Prasad S.

    2015-01-01

    Crop biomass is increasingly being measured with surface reflectance data derived from multispectral broadband (MSBB) and hyperspectral narrowband (HNB) space-borne remotely sensed data to increase the accuracy and efficiency of crop yield models used in a wide array of agricultural applications. However, few studies compare the ability of MSBBs versus HNBs to capture crop biomass variability. Therefore, we used standard data mining techniques to identify a set of MSBB data from the IKONOS, GeoEye-1, Landsat ETM+, MODIS, WorldView-2 sensors and compared their performance with HNB data from the EO-1 Hyperion sensor in explaining crop biomass variability of four important field crops (rice, alfalfa, cotton, maize). The analysis employed two-band (ratio) vegetation indices (TBVIs) and multiband (additive) vegetation indices (MBVIs) derived from Singular Value Decomposition (SVD) and stepwise regression. Results demonstrated that HNB-derived TBVIs and MBVIs performed better than MSBB-derived TBVIs and MBVIs on a per crop basis and for the pooled data: overall, HNB TBVIs explained 5–31% greater variability when compared with various MSBB TBVIs; and HNB MBVIs explained 3–33% greater variability when compared with various MSBB MBVIs. The performance of MSBB MBVIs and TBVIs improved mildly, by combining spectral information across multiple sensors involving IKONOS, GeoEye-1, Landsat ETM+, MODIS, and WorldView-2. A number of HNBs that advance crop biomass modeling were determined. Based on the highest factor loadings on the first component of the SVD, the “red-edge” spectral range (700–740 nm) centered at 722 nm (bandwidth = 10 nm) stood out prominently, while five additional and distinct portions of the recorded spectral range (400–2500 nm) centered at 539 nm, 758 nm, 914 nm, 1130 nm, 1320 nm (bandwidth = 10 nm) were also important. The best HNB vegetation indices for crop biomass estimation involved 549 and 752 nm for rice (R2 = 0.91); 925 and 1104 nm for

  18. Losses Assessment of Crops due to Typhoon Disaster in China Coastal Areas —— A Case Study of Zhanjiang City, Guangdong Province

    NASA Astrophysics Data System (ADS)

    Mo, W.; Fang, W.

    2015-12-01

    Vulnerability which quantifies the loss ratio under different hazard intensity is an important feature of the natural disaster system and has important significance to natural disaster risk assessment. Agriculture is an outdoor industry with high risk of meteorological disasters. The strong winds, heavy rain and storm surge are main typhoon hazard factors to crops. To provide a quantitative research method for the loss evaluation of crops due to typhoon disaster we first revised two vulnerability curves for crops under comprehensive intensity of typhoon based on the simulated hazard data and loss data related to historical typhoon events landing on China from 1949 to 2014;and then established a storm surge vulnerability matrix of crops regarding Zhanjiang City of Guangdong Province as the study area ; finally, we put forward three storm surge fragility curves for crops representing different states of loss. The results can effectively describe the typhoon vulnerability for crops in China coastal areas so as to provide the input to post-disaster loss assessments and catastrophe modeling applications.

  19. An estimation of annual nitrous oxide emissions and soil quality following the amendment of high temperature walnut shell biochar and compost to a small scale vegetable crop rotation.

    PubMed

    Suddick, Emma C; Six, Johan

    2013-11-01

    Agricultural soils are responsible for emitting large quantities of nitrous oxide (N2O). The controlled incomplete thermal decomposition of agricultural wastes to produce biochar, once amended to soils, have been hypothesized to increase crop yield, improve soil quality and reduce N2O emissions. To estimate crop yields, soil quality parameters and N2O emissions following the incorporation of a high temperature (900 °C) walnut shell (HTWS) biochar into soil, a one year field campaign with four treatments (control (CONT), biochar (B), compost (COM), and biochar+compost (B+C)) was conducted in a small scale vegetable rotation system in Northern California. Crop yields from five crops (lettuce, winter cover crop, lettuce, bell pepper and Swiss chard) were determined; there were no significant differences in yield between treatments. Biochar amended soils had significant increases in % total carbon (C) and the retention of potassium (K) and calcium (Ca). Annual cumulative N2O fluxes were not significantly different between the four treatments with emissions ranging from 0.91 to 1.12 kg N2O-N ha(-1) yr(-1). Distinct peaks of N2O occurred upon the application of N fertilizers and the greatest mean emissions, ranging from 67.04 to 151.41 g N2O-N ha(-1) day(-1), were observed following the incorporation of the winter cover crop. In conclusion, HTWS biochar application to soils had a pronounced effect on the retention of exchangeable cations such as K and Ca compared to un-amended soils and composted soils, which in turn could reduce leaching of these plant available cations and could thus improve soils with poor nutrient retention. However, HTWS biochar additions to soil had neither a positive or negative effect on crop yield nor cumulative annual emissions of N2O.

  20. An estimation of annual nitrous oxide emissions and soil quality following the amendment of high temperature walnut shell biochar and compost to a small scale vegetable crop rotation.

    PubMed

    Suddick, Emma C; Six, Johan

    2013-11-01

    Agricultural soils are responsible for emitting large quantities of nitrous oxide (N2O). The controlled incomplete thermal decomposition of agricultural wastes to produce biochar, once amended to soils, have been hypothesized to increase crop yield, improve soil quality and reduce N2O emissions. To estimate crop yields, soil quality parameters and N2O emissions following the incorporation of a high temperature (900 °C) walnut shell (HTWS) biochar into soil, a one year field campaign with four treatments (control (CONT), biochar (B), compost (COM), and biochar+compost (B+C)) was conducted in a small scale vegetable rotation system in Northern California. Crop yields from five crops (lettuce, winter cover crop, lettuce, bell pepper and Swiss chard) were determined; there were no significant differences in yield between treatments. Biochar amended soils had significant increases in % total carbon (C) and the retention of potassium (K) and calcium (Ca). Annual cumulative N2O fluxes were not significantly different between the four treatments with emissions ranging from 0.91 to 1.12 kg N2O-N ha(-1) yr(-1). Distinct peaks of N2O occurred upon the application of N fertilizers and the greatest mean emissions, ranging from 67.04 to 151.41 g N2O-N ha(-1) day(-1), were observed following the incorporation of the winter cover crop. In conclusion, HTWS biochar application to soils had a pronounced effect on the retention of exchangeable cations such as K and Ca compared to un-amended soils and composted soils, which in turn could reduce leaching of these plant available cations and could thus improve soils with poor nutrient retention. However, HTWS biochar additions to soil had neither a positive or negative effect on crop yield nor cumulative annual emissions of N2O. PMID:23490323

  1. Variations of carbonaceous aerosols from open crop residue burning with transport and its implication to estimate their lifetimes

    NASA Astrophysics Data System (ADS)

    Pan, X. L.; Kanaya, Y.; Wang, Z. F.; Komazaki, Y.; Taketani, F.; Akimoto, H.; Pochanart, P.

    2013-08-01

    Studying the correlations of carbonaceous aerosols (element carbon, EC, and organic carbon, OC) from open biomass burning helps to reduce uncertainties in emission inventories and provides necessary constraints for model simulations. In the present study, we measured apparent elemental carbon (ECa) and OC concentrations at the summit of Mount Tai (Mt. Tai) during intensive open crop residue burning (OCRB) episodes using a Sunset OCEC analyzer. In the fine particle mode, OC and ECa showed strong correlations (r > 0.9) with carbon monoxide (CO). Footprint analysis using the FLEXPART_WRF model indicated that OCRB in Central East China had a significant influence on ambient carbonaceous aerosol loadings at the summit of Mt. Tai. During campaign, ΔECa/ΔCO ratios of OCRB plumes were found to be 14.3 ± 1.0 ng m-3 ppbv at Mt. Tai. This ratio was twice larger than those for urban pollution in CEC, demonstrating that significant emissions of soot particles emitted from OCRB. ΔOC/ΔCO ratio of OCRB plumes was found to be 41.9 ± 2.6 ng m-3 ppbv averagely. The transport time of smoke particles was estimated using the FLEXPART_WRF tracer model by releasing particles from the ground layer inside geographical regions where large numbers of hotspots were detected by the MODIS sensor. The relationship between transport time and observed ΔECa/ΔCO and ΔOC/ΔCO ratios was fitted by an e-folding exponential function. Results showed that the loss rate of OC (normalized by CO) with transport was much quicker than that of ECa mass, and the corresponding lifetime of OC mass was estimated to be 28.0-44.2 h (1.2-1.8 days), much shorter than that 98.4-136.9 h (4.1-5.7 days) of ECa. Lifetime of ECa estimated for the OCRB events in CEC in the study was comparably lower than the values normally calculated by the transport models. Short lifetime of OC highlighted its vulnerability to cloud scavenging in the presence of water-soluble organic species from biomass combustion.

  2. Estimation of the change in the harmfulness of selected pests in expected climate - European area

    NASA Astrophysics Data System (ADS)

    Svobodova, E.; Trnka, M.; Zalud, Z.; Semeradova, D.; Dubrovsky, M.; Sefrova, H.

    2010-09-01

    Climate change is likely to be a dominant factor affecting the lifecycle and overall occurrence of pest's species whose development is directly linked with climate conditions. This study is focused on the estimation of the potential occurrence and generation growth of selected pests causing the significant damages on the yield of crops over western part of Europe in changing climate. Modelled species involved the main pest of potato Colorado potato beetle (Leptinotarsa decemlineata, Say 1824), the pest of maize European corn borer (Ostrinia nubilalis, Hubner 1796), the pest which causes the damages in orchards and decreases the yield of apples, Codling moth (Cydia pomonella, Linnaeus 1758) and Cereal leaf beetle (Oulema melanopus, Linnaeus 1758) seriously affecting wheat production. The development of these pests' is driven mainly by temperature of the environment, which is in turn function of air temperature. The climate change is likely to lead to an earlier once and prolongation of the growing season and in the same time accelerate pests' developmental rate and will increase number of generations. Estimates of potential distribution of selected pest species for the present as well as expected climate conditions are based on the dynamical model CLIMEX. This approach exploits the expression of the overall climate suitability for the species longterm survival in terms of ecoclimatic index. The CLIMEX model was at first validated with observed data of pests' occurrences using CRU 10´ climate data set a source of climate data. All pest models listed were then used to study the effects of climate change on pests by estimating changes in population dynamics and/or infestation pressure during the first half of the 21st century. Outputs of the models were applied within the European scale in the 10´ resolution using digital terrain model. Simulations of the impacts of expected climate on the pests distribution were conducted under three global circulation models (Had

  3. Small area estimation (SAE) model: Case study of poverty in West Java Province

    NASA Astrophysics Data System (ADS)

    Suhartini, Titin; Sadik, Kusman; Indahwati

    2016-02-01

    This paper showed the comparative of direct estimation and indirect/Small Area Estimation (SAE) model. Model selection included resolve multicollinearity problem in auxiliary variable, such as choosing only variable non-multicollinearity and implemented principal component (PC). Concern parameters in this paper were the proportion of agricultural venture poor households and agricultural poor households area level in West Java Province. The approach for estimating these parameters could be performed based on direct estimation and SAE. The problem of direct estimation, three area even zero and could not be conducted by directly estimation, because small sample size. The proportion of agricultural venture poor households showed 19.22% and agricultural poor households showed 46.79%. The best model from agricultural venture poor households by choosing only variable non-multicollinearity and the best model from agricultural poor households by implemented PC. The best estimator showed SAE better then direct estimation both of the proportion of agricultural venture poor households and agricultural poor households area level in West Java Province. The solution overcame small sample size and obtained estimation for small area was implemented small area estimation method for evidence higher accuracy and better precision improved direct estimator.

  4. Phosphorus Retention by Stormwater Detention Areas: Estimation, Enhancement, and Economics

    NASA Astrophysics Data System (ADS)

    Shukla, A.; Shukla, S.; Hodges, A.

    2015-12-01

    Stormwater detention areas (SDAs) are considered an important best management practice (BMP) both in agricultural and urban areas. In sub-tropical Florida where sandy soils and shallow water table make the nutrient leaching losses from agricultural areas inevitable, the SDAs are relied upon as a last point of treatment. Field-measured water and phosphorus (P) fluxes from an agricultural SDA showed that contrary to generally held view, the SDA was a source of P for the first year (retention efficiency = -12%). For the next year, the SDA served as a sink (54%). The source function of the SDA was a combined effect of high rainfall, dilution of agricultural drainage with rainfall from a tropical storm, and legacy-based soil P saturation. Volume reduction was the main reason for P retention because of no remaining P sorption capacity in the soil in most of the SDA area. Although a net sink of P for Year 2, an event-wise analysis showed the SDA to be a source of P for three out of seven outflow events in Year 2 indicating P release from soil. Because surface P treatment efficiency during both years was either less than or approximately the same as surface water retention efficiency, volume reduction and not sorption or biological assimilation controlled P retention. Hydraulic (e.g. increased storage), managerial (biomass harvesting) and chemical (alum treatment) modifications were evaluated by using a stormwater treatment model and field data. The model was successfully field-verified using well accepted performance measures (e.g. Nash-Sutcliffe efficiency). Maximum additional P retention was shown to be achieved by biomass harvesting (>100%) followed by chemical treatment (71%), and increased spillage level (29%). Economic feasibility of the aforementioned modifications and development of a payment for environmental services (PES) program was identified through a cost-benefit analysis for maintaining these SDAs as sink of P in the long-term.

  5. Research in satellite-aided crop forecasting

    NASA Technical Reports Server (NTRS)

    Erickson, J. D.; Dragg, J. L.; Bizzell, R. M.; Trichel, M. C.

    1984-01-01

    Evaluations of remote sensing procedures developed specifically to estimate non-U.S. spring small grains area show accuracies of less than 10 percent relative difference to reference statistics for North Dakota in 1978 and good comparison with 9000 square miles of observations over four states and Saskatchewan, Canada during the years 1976-79. Processing a 5 x 6-nautical-mile sample site requires a few minutes manual time and a few minutes central processing unit time on an AS-3000 computer. Evaluations of summer crop, corn, and soybeans area estimates show unbiased summer crops estimates in the U.S. central corn belt but significant bias in one of two years for area estimates of corn and soybeans. Based on results to date, a highly automated corn/sorghum/soybean area estimation procedure should be achieved that is applicable to Argentina.

  6. Leaf Area Index Estimation in Vineyards from Uav Hyperspectral Data, 2d Image Mosaics and 3d Canopy Surface Models

    NASA Astrophysics Data System (ADS)

    Kalisperakis, I.; Stentoumis, Ch.; Grammatikopoulos, L.; Karantzalos, K.

    2015-08-01

    The indirect estimation of leaf area index (LAI) in large spatial scales is crucial for several environmental and agricultural applications. To this end, in this paper, we compare and evaluate LAI estimation in vineyards from different UAV imaging datasets. In particular, canopy levels were estimated from i.e., (i) hyperspectral data, (ii) 2D RGB orthophotomosaics and (iii) 3D crop surface models. The computed canopy levels have been used to establish relationships with the measured LAI (ground truth) from several vines in Nemea, Greece. The overall evaluation indicated that the estimated canopy levels were correlated (r2 > 73%) with the in-situ, ground truth LAI measurements. As expected the lowest correlations were derived from the calculated greenness levels from the 2D RGB orthomosaics. The highest correlation rates were established with the hyperspectral canopy greenness and the 3D canopy surface models. For the later the accurate detection of canopy, soil and other materials in between the vine rows is required. All approaches tend to overestimate LAI in cases with sparse, weak, unhealthy plants and canopy.

  7. Soil arsenic availability and the transfer of soil arsenic to crops in suburban areas in Fujian Province, southeast China.

    PubMed

    Huang, Rui-Qing; Gao, Shu-Fang; Wang, Wei-Ling; Staunton, S; Wang, Guo

    2006-09-15

    The bioavailability, soil-to-plant transfer and associated health risks of arsenic in soils collected from paddy rice fields and vegetable fields in suburban areas of some major cities of Fujian Province were investigated. The total soil concentrations of arsenic ranged from 1.29 to 25.28 mg kg(-)(1) with a mean of 6.09 mg kg(-)(1). Available (NaH(2)PO(4)-extractable) arsenic content accounted for 0.7-38.2% of total soil arsenic and was significantly correlated with total soil arsenic content. For the vegetable soils, the available fraction (ratio of available As to total As) of arsenic decreased with decreasing silt (particle size 0.02-0.002 mm) and free iron (DCB extractable) contents and with increasing soil pH and organic matter content. The available fraction of arsenic in the paddy rice soils increased with increasing free iron and organic matter contents and decreasing soil pH and silt content. The correlation of NaH(2)PO(4)-extractable arsenic with the arsenic concentration of the vegetables was much better than that of total As. The transfer factor based on the soil available arsenic (TF(avail)) was chosen to compare the accumulation ability of the various crops. The TF(avail) values of rice grains (air-dried weight basis) ranged between 0.068 and 0.44 and were higher than those of the vegetables, ranging from 0.001 to 0.12. The accumulation ability of the crops decreased in the order of rice>radish>water spinach>celery>onion>taro>leaf mustard>fragrant-flowered garlic>pakchoi>Chinese cabbage>lettuce>garlic>cowpea>cauliflower>bottle gourd>towel gourd>eggplant. Daily consumption of rice and other As-rich vegetables could result in an excessive intake of arsenic, based on the provisional tolerable intake for adults for arsenic recommended by WHO. PMID:16624379

  8. Changes of water demand - possible adaptation of agricultural crops and management options to improve water use efficiency in the Marchfeld area

    NASA Astrophysics Data System (ADS)

    Thaler, S.; Eitzinger, J.; Dubrovsky, M.; Trnka, M.

    2009-04-01

    The main objective of this study was to determine the vulnerability of current agricultural cropping systems in the Marchfeld region to climate change. The investigation area Marchfeld is located in the north-eastern (NE) part of Austria and is characterized by a semi-arid climate with low annual rainfall. It is one of the driest regions in the country, but also one of the main field crop production areas. The soil conditions in Marchfeld demonstrate a significant spatial variability, which include soils with low to moderate water-storage capacities. Higher temperatures in the next decades imply higher evaporation and consequently higher water demand for the crops. The phenological development rates of the cultivars will accelerate and an increase of heat stress as well as drought stress can be expected. These points influence intense the water balance and subsequently the yield of the crops in the investigation area. In order to improve water use efficiency under those changing conditions, a shift of average sowing dates and an adjustment of tillage were analyzed. The DSSAT cropping system model was applied for winter wheat and spring barley to assess potential yield under climate scenarios for NE Austria. The scenarios were carried out with ECHAM5, HadCM3 and NCAR PCM global circulation models (GCMs) for present conditions (reference period 1961-1990) and 2035's (2021-2050), based on SRES-A1B emission scenarios. Yield model simulations were done for all defined scenarios (climate, management, crop) and different soil classes. The simulations contain the CO2 fertilizing effect, rain fed farming, adapted sowing date and contemporary crops without consideration of potential profit cuts caused by pest or diseases. Simulation results indicate that climate change will force a delay of the sowing date for winter wheat of maximal 14 days in October. In case of spring barley, climate change allows an earlier sowing date in spring (up to 14 days). Both crops show a

  9. Estimating vehicle fuel consumption in urban areas. Working paper

    SciTech Connect

    Ferreira, L.J.A.

    1981-01-01

    Traffic flow simulation and assignment techniques were used to model area-wide effects of traffic management measures. Relationships between fuel consumption under urban driving conditions and the inverse of average travel speed were inferred from experimental tests. From the results a relationship which gave urban fuel consumption as a function of journey distance, total delayed time, and number of stops, was suggested for the 'average urban passenger car' in the UK. A review of reported potential fuel savings from traffic management measures was also undertaken. The effects on fuel consumption of changing the common cycle time for a co-ordinated system of signalised intersections were evaluated using the SATURN traffic simulation/assignment model.

  10. Estimation of lifetime of carbonaceous aerosol from open crop residue burning during Mount Tai Experiment 2006 (MTX2006)

    NASA Astrophysics Data System (ADS)

    Pan, X. L.; Kanaya, Y.; Wang, Z. F.; Komazaki, Y.; Taketani, F.; Akimoto, H.; Pochanart, P.; Liu, Y.

    2012-06-01

    Studying the emission ratios of carbonaceous aerosols (element carbon, EC, and organic carbon, OC) from open biomass burning helps to reduce uncertainties in emission inventories and provides necessary constraints for model simulations. We measured apparent elemental carbon (ECa) and OC concentrations at the summit of Mount Tai (Mt. Tai) during intensive open crop residue burning (OCRB) episodes using a Sunset OCEC analyzer. Equivalent black carbon (BCe) concentrations were determined using a Multiple Angle Absorption Photometer (MAAP). In the fine particle mode, OC and EC showed strong correlations (r > 0.9) with carbon monoxide (CO). Footprint analysis using the FLEXPART_WRF model indicated that OCRB in central east China (CEC) had a significant influence on ambient carbonaceous aerosol loadings at the summit of Mt. Tai. ΔECa/ΔCO ratios resulting from OCRB plumes were 14.3 ± 1.0 ng m-3 ppbv-1 at Mt. Tai. This ratio was more than three times those resulting from urban pollution in CEC, demonstrating that significant concentrations of soot particles were released from OCRB. ΔOC/ΔCO ratio from fresh OCRB plumes was found to be 41.9 ± 2.6 ng m-3 ppbv-1 in PM1. The transport time of smoke particles was estimated using the FLEXPART_WRF tracer model by releasing inert particles from the ground layer inside geographical regions where large numbers of hotspots were detected by a MODIS satellite sensor. Fitting regressions using the e-folding exponential function indicated that the removal efficiency of OC (normalized to CO) was much larger than that of ECa mass, with mean lifetimes of 27 h (1.1 days) for OC and 105 h (4.3 days) for ECa, respectively. The lifetime of black carbon estimated for the OCRB events in east China was comparably lower than the values normally adopted in the transport models. Short lifetime of organic carbon highlighted the vulnerability of OC to cloud scavenging in the presence of water-soluble organic species from biomass combustion.

  11. Potential and limitations of spectral reflectance measurements for the estimation of the site-specific variability in crops

    NASA Astrophysics Data System (ADS)

    Erasmi, Stefan; Dobers, Eike S.

    2004-02-01

    The use of remote sensing data in site specific crop management aims at the prediction of soil and crop factors that have an impact on yield formation processes in agriculture. Numerous methods demonstrate the potential of spectral reflectance data for the detection of qualitative and quantitative crop features but there is, however, no established methodology for the implementation of these data in operational crop production processes. The paper describes the main aspects of remote sensing based site characterization, considering major site variables (yield, soil) and plant parameters (nitrogen uptake) as key features for the description of the site specific variability in crops. Spectral reflectance data of the VIS/NIR region are transformed into different spectral indices for statistical analysis. Analyzing these indices it is found that the determination of a prediction model depends on the relevance of the suggested data fitting method (causality) as well as on the statistical significance of the interrelationship. Results point out that remote sensing data are suitable predictors for crop vitality and site characterization. Hence, the application of these data in agricultural work routines is limited by their quality and availability as well as by the influence of environmental factors on yield formation processes.

  12. Distribution of inorganic phosphorus in profiles and particle-size fractions across an established riparian buffer and adjacent cropped area at the Dian lake

    NASA Astrophysics Data System (ADS)

    Zhang, G. S.; Li, J. C.

    2015-11-01

    Riparian buffer can trap sediment and nutrients sourced from upper cropland and minimizing eutrophication risk of water quality. This study aimed to investigate the distributions of soil inorganic phosphorus (Pi) forms among profile and particle-size fractions in an established riparian buffer and adjacent cropped area at the Dian lake, Southwestern China. The Ca-bound fraction (62 %) was the major proportion of the Pi in the riparian soils. Buffer rehabilitation from cropped area had a limited impact on total phosphorus (TP) concentrations after 3 years, but has contributed to a change in Pi forms. At 0-20 cm soil layer, levels of the Olsen-P, nonoccluded, Ca-bound and total Pi were lower in the buffer than the cropped area; however, the Pi distribution between the cropped area and the buffer did not differ significantly as depth increased. The clay fraction corresponded to 57 % of TP and seemed to be both a sink for highly recalcitrant Pi and a source for labile Pi. The lower concentration of Pi forms in the silt and sand particle fraction in the surface soil was observed in the buffer area, which indicating that the Pi distribution in coarse particle fraction has sensitively responded to land-use changes.

  13. Distribution of inorganic phosphorus in profiles and particle fractions of Anthrosols across an established riparian buffer and adjacent cropped area at the Dian lake (China)

    NASA Astrophysics Data System (ADS)

    Zhang, Guo Sheng; Cha Li, Jian

    2016-02-01

    Riparian buffers can trap sediment and nutrients sourced from upper cropland, minimizing the eutrophication risk of water quality. This study aimed to investigate the distributions of soil inorganic phosphorus (Pi) forms among profile and particle-size fractions in an established riparian buffer and adjacent cropped area at the Dian lake, southwestern China. The Ca-bound fraction (62 %) was the major proportion of the Pi in the riparian soils. After 3 years' restoration, buffer rehabilitation from cropped area had a limited impact on total phosphorus (TP) concentrations, but has contributed to a change in Pi forms. In the 0-20 cm soil layer, levels of the Olsen-P, non-occluded, Ca-bound, and total Pi were lower in the buffer than the cropped area; however, the Pi distribution between the cropped area and the buffer did not differ significantly as depth increased. The clay fraction corresponded to 57 % of TP and seemed to be both a sink for highly recalcitrant Pi and a source for labile Pi. The lower concentration of Pi forms in the silt and sand particle fraction in the surface soil was observed in the buffer area, which indicated that the Pi distribution in coarse particle fraction had sensitively responded to land use changes.

  14. A TRMM Rainfall Estimation Method Applicable to Land Areas

    NASA Technical Reports Server (NTRS)

    Prabhakara, C.; Iacovazzi, R., Jr.; Oki, R.; Weinman, J. A.

    1998-01-01

    Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that

  15. [Arsenic contents in soil, water, and crops in an e-waste disposal area].

    PubMed

    Yao, Chun-xia; Yin, Xue-bin; Song, Jing; Li, Chen-xi; Qian, Wei; Zhao, Qi-guo; Luo, Yong-ming

    2008-06-01

    In order to study whether disposing electronic wastes and secondary metal smelting could cause an arsenic pollution in the environment or not, Luqiao town, Taizhou City, Zhejiang Province was selected as a study area. The main purpose of this paper was to characterize arsenic contents in the local environment, including waters, sediments, soils and rice, and to assess the potential risk to humans. Additionally, the arsenic spatial distribution property and arsenic uptake-translocation rule in soil-rice system were also studied. The results showed that the average arsenic levels in the surface water and the groundwater were 8.26 microg/L and 18.52 microg/L, respectively, which did not exceed the limiting value of Chinese Environment Standards class III . Whereas,some groundwater exceeded the recommended standard by the WHO for drinking water (10 microg/L). The arsenic (on average 7.11 mg/kg) in paddy soils and arsenic (on average 6.17 mg/kg) in the vegetable garden soils were lower than the value recommended by the National Standard (level I). The average arsenic contents in brown rice and husks were 165.1 microg/kg and 144.2 microg/kg, which was also lower than the Chinese Foods Quality Standard. The arsenic contents between the corresponding soils-rice and husks-brown rice showed significantly positive correlations. By comparison, the arsenic contents of soils and husks collected around electroplating were relatively higher than most of other pollutant sources, indicating the electroplating may lead accumulation of arsenic in the paddy soil-rice system. PMID:18763528

  16. [Arsenic contents in soil, water, and crops in an e-waste disposal area].

    PubMed

    Yao, Chun-xia; Yin, Xue-bin; Song, Jing; Li, Chen-xi; Qian, Wei; Zhao, Qi-guo; Luo, Yong-ming

    2008-06-01

    In order to study whether disposing electronic wastes and secondary metal smelting could cause an arsenic pollution in the environment or not, Luqiao town, Taizhou City, Zhejiang Province was selected as a study area. The main purpose of this paper was to characterize arsenic contents in the local environment, including waters, sediments, soils and rice, and to assess the potential risk to humans. Additionally, the arsenic spatial distribution property and arsenic uptake-translocation rule in soil-rice system were also studied. The results showed that the average arsenic levels in the surface water and the groundwater were 8.26 microg/L and 18.52 microg/L, respectively, which did not exceed the limiting value of Chinese Environment Standards class III . Whereas,some groundwater exceeded the recommended standard by the WHO for drinking water (10 microg/L). The arsenic (on average 7.11 mg/kg) in paddy soils and arsenic (on average 6.17 mg/kg) in the vegetable garden soils were lower than the value recommended by the National Standard (level I). The average arsenic contents in brown rice and husks were 165.1 microg/kg and 144.2 microg/kg, which was also lower than the Chinese Foods Quality Standard. The arsenic contents between the corresponding soils-rice and husks-brown rice showed significantly positive correlations. By comparison, the arsenic contents of soils and husks collected around electroplating were relatively higher than most of other pollutant sources, indicating the electroplating may lead accumulation of arsenic in the paddy soil-rice system.

  17. Impact of climate change estimated through statistical downscaling on crop productivity and soil water balance in Southern Italy

    NASA Astrophysics Data System (ADS)

    Ventrella, D.; Giglio, L.; Charfeddine, M.; Palatella, L.; Pizzigalli, C.; Vitale, D.; Paradisi, P.; Miglietta, M. M.; Rana, G.

    2010-09-01

    The climatic change induced by the global warming is expected to modify the agricultural activity and consequently the other social and economical sectors. In this context, an efficient management of the water resources is considered very important for Italy and in particular for Southern areas characterized by a typical Mediterranean climate in order to improve the economical and environmental sustainability of the agricultural activity. Climate warming could have a substantial impact on some agronomical practices as the choice of the crops to be included in the rotations, the sowing time and the irrigation scheduling. For a particular zone, the impact of climatic change on agricultural activity will depend also on the continuum "soil-plant-climate" and this continuum has to be included in the analysis for forecasting purposes. The Project CLIMESCO is structured in four workpackages (WP): (1) Identification of homogeneous areas, (2) Climatic change, (3) Optimization of water resources and (4) Scenarios analysis. In this study we applied a statistical downscaling method, Canonical Correlation Analysis after Principal Component Analysis filtering, to two sub-regions of agricultural interest in Sicily and Apulia (respectively, Delia basin and Capitanata). We adopt, as large scale predictors, the sea level pressure from the the EMULATE project dataset and the 1000 hPa temperature obtained from the NCEP reanalyses, while the predictands are monthly time series of maximum and minimum temperature and precipitation. As the crop growth models need daily datasets, a stochastic weather generator (the LARS-WG model) has been applied for this purpose. LARS-WG needs a preliminary calibration with daily time series of meteorological fields, that are available in the framework of CLIMESCO project. Then, the statistical relationships have been applied to two climate change scenarios (SRES A2 and B2), provided by three different GCM's: the Hadley Centre Coupled Model version 3 (Had

  18. Evaluating Crop Area Mapping from MODIS Time-Series as an Assessment Tool for Zimbabwe's "Fast Track Land Reform Programme".

    PubMed

    Hentze, Konrad; Thonfeld, Frank; Menz, Gunter

    2016-01-01

    Moderate Resolution Imaging Spectroradiometer (MODIS) data forms the basis for numerous land use and land cover (LULC) mapping and analysis frameworks at regional scale. Compared to other satellite sensors, the spatial, temporal and spectral specifications of MODIS are considered as highly suitable for LULC classifications which support many different aspects of social, environmental and developmental research. The LULC mapping of this study was carried out in the context of the development of an evaluation approach for Zimbabwe's land reform program. Within the discourse about the success of this program, a lack of spatially explicit methods to produce objective data, such as on the extent of agricultural area, is apparent. We therefore assessed the suitability of moderate spatial and high temporal resolution imagery and phenological parameters to retrieve regional figures about the extent of cropland area in former freehold tenure in a series of 13 years from 2001-2013. Time-series data was processed with TIMESAT and was stratified according to agro-ecological potential zoning of Zimbabwe. Random Forest (RF) classifications were used to produce annual binary crop/non crop maps which were evaluated with high spatial resolution data from other satellite sensors. We assessed the cropland products in former freehold tenure in terms of classification accuracy, inter-annual comparability and heterogeneity. Although general LULC patterns were depicted in classification results and an overall accuracy of over 80% was achieved, user accuracies for rainfed agriculture were limited to below 65%. We conclude that phenological analysis has to be treated with caution when rainfed agriculture and grassland in semi-humid tropical regions have to be separated based on MODIS spectral data and phenological parameters. Because classification results significantly underestimate redistributed commercial farmland in Zimbabwe, we argue that the method cannot be used to produce spatial

  19. Advancing the climate data driven crop-modeling studies in the dry areas of Northern Syria and Lebanon: an important first step for assessing impact of future climate.

    PubMed

    Dixit, Prakash N; Telleria, Roberto

    2015-04-01

    Inter-annual and seasonal variability in climatic parameters, most importantly rainfall, have potential to cause climate-induced risk in long-term crop production. Short-term field studies do not capture the full nature of such risk and the extent to which modifications to crop, soil and water management recommendations may be made to mitigate the extent of such risk. Crop modeling studies driven by long-term daily weather data can predict the impact of climate-induced risk on crop growth and yield however, the availability of long-term daily weather data can present serious constraints to the use of crop models. To tackle this constraint, two weather generators namely, LARS-WG and MarkSim, were evaluated in order to assess their capabilities of reproducing frequency distributions, means, variances, dry spell and wet chains of observed daily precipitation, maximum and minimum temperature, and solar radiation for the eight locations across cropping areas of Northern Syria and Lebanon. Further, the application of generated long-term daily weather data, with both weather generators, in simulating barley growth and yield was also evaluated. We found that overall LARS-WG performed better than MarkSim in generating daily weather parameters and in 50 years continuous simulation of barley growth and yield. Our findings suggest that LARS-WG does not necessarily require long-term e.g., >30 years observed weather data for calibration as generated results proved to be satisfactory with >10 years of observed data except in area with higher altitude. Evaluating these weather generators and the ability of generated weather data to perform long-term simulation of crop growth and yield is an important first step to assess the impact of future climate on yields, and to identify promising technologies to make agricultural systems more resilient in the given region.

  20. Farmers' Perception of Integrated Soil Fertility and Nutrient Management for Sustainable Crop Production: A Study of Rural Areas in Bangladesh

    ERIC Educational Resources Information Center

    Farouque, Md. Golam; Takeya, Hiroyuki

    2007-01-01

    This study aimed to determine farmers' perception of integrated soil fertility and nutrient management for sustainable crop production. Integrated soil fertility (ISF) and nutrient management (NM) is an advanced approach to maintain soil fertility and to enhance crop productivity. A total number of 120 farmers from eight villages in four districts…

  1. Identification and estimation of the area planted with irrigated rice based on the visual interpretation of LANDSAT MSS data

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Moreira, M. A.; Assuncao, G. V.; Novaes, R. A.; Mendoza, A. A. B.; Bauer, C. A.; Ritter, I. T.; Barros, J. A. I.; Perez, J. E.; Thedy, J. L. O.

    1983-01-01

    The objective was to test the feasibility of the application of MSS-LANDSAT data to irrigated rice crop identification and area evaluation, within four rice growing regions of the Rio Grande do Sul state, in order to extend the methodology for the whole state. The applied methodology was visual interpretation of the following LANDSAT products: channels 5 and 7 black and white imageries and color infrared composite imageries all at the scale of 1:250.000. For crop identification and evaluation, the multispectral criterion and the seasonal variation were utilized. Based on the results it was possible to conclude that: (1) the satellite data were efficient for crop area identification and evaluation; (2) the utilization of the multispectral criterion, allied to the seasonal variation of the rice crop areas from the other crops and, (3) the large cloud cover percentage found in the satellite data made it impossible to realize a rice crop spectral monitoring and, therefore, to define the best dates for such data acquisition for rice crop assessment.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Nearing, G. S.; Crow, W. T.; Thorp, K. R.; Moran, M. S.; Reichle, R. H.; Gupta, H. V.

    2012-05-01

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

  4. Post-stratification sampling in small area estimation (SAE) model for unemployment rate estimation by Bayes approach

    NASA Astrophysics Data System (ADS)

    Hanike, Yusrianti; Sadik, Kusman; Kurnia, Anang

    2016-02-01

    This research implemented unemployment rate in Indonesia that based on Poisson distribution. It would be estimated by modified the post-stratification and Small Area Estimation (SAE) model. Post-stratification was one of technique sampling that stratified after collected survey data. It's used when the survey data didn't serve for estimating the interest area. Interest area here was the education of unemployment which separated in seven category. The data was obtained by Labour Employment National survey (Sakernas) that's collected by company survey in Indonesia, BPS, Statistic Indonesia. This company served the national survey that gave too small sample for level district. Model of SAE was one of alternative to solved it. According the problem above, we combined this post-stratification sampling and SAE model. This research gave two main model of post-stratification sampling. Model I defined the category of education was the dummy variable and model II defined the category of education was the area random effect. Two model has problem wasn't complied by Poisson assumption. Using Poisson-Gamma model, model I has over dispersion problem was 1.23 solved to 0.91 chi square/df and model II has under dispersion problem was 0.35 solved to 0.94 chi square/df. Empirical Bayes was applied to estimate the proportion of every category education of unemployment. Using Bayesian Information Criteria (BIC), Model I has smaller mean square error (MSE) than model II.

  5. Evaluation of the transfer of soil arsenic to maize crops in suburban areas of San Luis Potosi, Mexico.

    PubMed

    Rosas-Castor, J M; Guzmán-Mar, J L; Alfaro-Barbosa, J M; Hernández-Ramírez, A; Pérez-Maldonado, I N; Caballero-Quintero, A; Hinojosa-Reyes, L

    2014-11-01

    The presence of arsenic (As) in agricultural food products is a matter of concern because it can cause adverse health effects at low concentrations. Agricultural-product intake constitutes a principal source for As exposure in humans. In this study, the contribution of the chemical-soil parameters in As accumulation and translocation in the maize crop from a mining area of San Luis Potosi was evaluated. The total arsenic concentration and arsenic speciation were determined by HG-AFS and IC-HG-AFS, respectively. The data analysis was conducted by cluster analysis (CA) and principal component analysis (PCA). The soil pH presented a negative correlation with the accumulated As in each maize plant part, and parameters such as iron (Fe) and manganese (Mn) presented a higher correlation with the As translocation in maize. Thus, the metabolic stress in maize may induce organic acid exudation leading a higher As bioavailability. A high As inorganic/organic ratio in edible maize plant tissues suggests a substantial risk of poisoning by this metalloid. Careful attention to the chemical changes in the rhizosphere of the agricultural zones that can affect As transfer through the food chain could reduce the As-intoxication risk of maize consumers. PMID:25128885

  6. Evaluation of the transfer of soil arsenic to maize crops in suburban areas of San Luis Potosi, Mexico.

    PubMed

    Rosas-Castor, J M; Guzmán-Mar, J L; Alfaro-Barbosa, J M; Hernández-Ramírez, A; Pérez-Maldonado, I N; Caballero-Quintero, A; Hinojosa-Reyes, L

    2014-11-01

    The presence of arsenic (As) in agricultural food products is a matter of concern because it can cause adverse health effects at low concentrations. Agricultural-product intake constitutes a principal source for As exposure in humans. In this study, the contribution of the chemical-soil parameters in As accumulation and translocation in the maize crop from a mining area of San Luis Potosi was evaluated. The total arsenic concentration and arsenic speciation were determined by HG-AFS and IC-HG-AFS, respectively. The data analysis was conducted by cluster analysis (CA) and principal component analysis (PCA). The soil pH presented a negative correlation with the accumulated As in each maize plant part, and parameters such as iron (Fe) and manganese (Mn) presented a higher correlation with the As translocation in maize. Thus, the metabolic stress in maize may induce organic acid exudation leading a higher As bioavailability. A high As inorganic/organic ratio in edible maize plant tissues suggests a substantial risk of poisoning by this metalloid. Careful attention to the chemical changes in the rhizosphere of the agricultural zones that can affect As transfer through the food chain could reduce the As-intoxication risk of maize consumers.

  7. Estimation of unemployment rates using small area estimation model by combining time series and cross-sectional data

    NASA Astrophysics Data System (ADS)

    Muchlisoh, Siti; Kurnia, Anang; Notodiputro, Khairil Anwar; Mangku, I. Wayan

    2016-02-01

    Labor force surveys conducted over time by the rotating panel design have been carried out in many countries, including Indonesia. Labor force survey in Indonesia is regularly conducted by Statistics Indonesia (Badan Pusat Statistik-BPS) and has been known as the National Labor Force Survey (Sakernas). The main purpose of Sakernas is to obtain information about unemployment rates and its changes over time. Sakernas is a quarterly survey. The quarterly survey is designed only for estimating the parameters at the provincial level. The quarterly unemployment rate published by BPS (official statistics) is calculated based on only cross-sectional methods, despite the fact that the data is collected under rotating panel design. The study purpose to estimate a quarterly unemployment rate at the district level used small area estimation (SAE) model by combining time series and cross-sectional data. The study focused on the application and comparison between the Rao-Yu model and dynamic model in context estimating the unemployment rate based on a rotating panel survey. The goodness of fit of both models was almost similar. Both models produced an almost similar estimation and better than direct estimation, but the dynamic model was more capable than the Rao-Yu model to capture a heterogeneity across area, although it was reduced over time.

  8. Using geocoded survey data to improve the accuracy of multilevel small area synthetic estimates.

    PubMed

    Taylor, Joanna; Moon, Graham; Twigg, Liz

    2016-03-01

    This paper examines the secondary data requirements for multilevel small area synthetic estimation (ML-SASE). This research method uses secondary survey data sets as source data for statistical models. The parameters of these models are used to generate data for small areas. The paper assesses the impact of knowing the geographical location of survey respondents on the accuracy of estimates, moving beyond debating the generic merits of geocoded social survey datasets to examine quantitatively the hypothesis that knowing the approximate location of respondents can improve the accuracy of the resultant estimates. Four sets of synthetic estimates are generated to predict expected levels of limiting long term illnesses using different levels of knowledge about respondent location. The estimates were compared to comprehensive census data on limiting long term illness (LLTI). Estimates based on fully geocoded data were more accurate than estimates based on data that did not include geocodes. PMID:26857175

  9. Estimation of Surface Area and Volume of a Nematode from Morphometric Data

    PubMed Central

    Brown, Simon; Pedley, Kevin C.; Simcock, David C.

    2016-01-01

    Nematode volume and surface area are usually based on the inappropriate assumption that the animal is cylindrical. While nematodes are approximately circular in cross section, the radius varies longitudinally. We use standard morphometric data to obtain improved estimates of volume and surface area based on (i) a geometrical approach and (ii) a Bézier representation of the nematode. These new estimators require only the morphometric data available from Cobb's ratios, but if fewer coordinates are available the geometric approach reduces to the standard estimates. Consequently, these new estimators are better than the standard alternatives. PMID:27110427

  10. Global Crop Area Monitoring at High Resolution Exploiting Complementary Use of Free and Open SAR and VSNIR/SWIR Sensor Data Sets

    NASA Astrophysics Data System (ADS)

    Lemoine, G.; LEO, O.

    2015-12-01

    Earth Observation imaging sensors with spatial resolutions in the 10-30 m range allow for separation of the area and crop status contributions to the radiometric signatures, typically at parcel level for a wide range of arable crop production systems. These sensors complement current monitoring efforts that deploy low (100-1000 m) resolution VSNIR/SWIR sensors like MODIS, METOP or PROBA-V, which provide denser time series, but with aggregated and mixed radiometric information for cropped areas. "Free and Open" access to US Landsat imagery has recently been complemented by the European Union's Copernicus program with access to Sentinel-1A C-band SAR and Sentinel-2A visual, near and short-ware infrared (VSNIR/SWIR) sensor data in the 10-20 m resolution range. Sentinel-1A has already proven that consistent time series can be generated at its 12 day revisit frequency. The density of Sentinel-2 time series will greatly expand the availability of [partially cloud covered] VSNIR/SWIR imagery. The release of this large new data flow coincides with wider availability of "big data" processing capacity, the public release of ever more detailed ancillary data sets that support extraction of georeferenced and robust indicators on crop production and their spatial and temporal statistics and developments in crowd-sourced mobile data collection for data validation purposes. We will illustrate the use of hybrid SAR and VSNIR/SWIR data sets from Sentinel-1 and Landsat-8 (and initially released Sentinel-2 imagery) for a number of selected examples. These include crop area delineation and classification in the Netherlands with the support of detailed parcel delineation sets for validation, detection of winter cereal cultivation in Ukraine, impact of the Syrian civil war on irrigated summer crop cultivation and recent examples in support to crop anomaly detection in food insecure areas (North Korea, Sub-Saharan Africa). We discuss method implementation, operational issues and outline

  11. A root zone model for estimating soil water balance and crop yield responses to deficit irrigation in the North China Plain

    NASA Astrophysics Data System (ADS)

    Ma, Y.; Song, X.; Feng, S.

    2012-12-01

    This study proposed a new soil water balance model by quantifying drainage out of the root zone with the simplification of the Darcy's law, which combined the advantages of conceptual and physically based models. This model was connected with the Jensen crop water production function to simulate soil water components and relative crop yield. Field experiments with the winter wheat-summer corn cropping system were conducted in Beijing area in the North China Plain (2007-2009) to evaluate the model. The model could give quite reasonable predictions of soil water content in the root zone with the average root mean square error (RMSE), mean relative error (RE) and model efficiency (EF) of 0.02 cm3/cm3, 6.69% and 0.78, respectively. Furthermore, the predicted soil water flux through the bottom of root zone agreed well with the measured ones supported by the values of RMSE (0.10 mm/d) and EF (0.92). The Jensen crop water production function with the calculated actual evapotranspitation from the soil water balance model could satisfactorily evaluate crop yield response to deficit irrigation with the EF values greater than 0.95 and the RE values lower than 6%. As an application, the model was used to obtain the optimal irrigation management schedules for the hydrologic years of 75%, 50% and 25% in the study area. The average amount of irrigation saving and reduction of water losses through drainage under optimal irrigation alternative were about 175 mm and 101.9 mm, respectively. This study indicates that the developed root zone model is more available for agricultural water management as it has minimal input requirement, robust physical meaning and satisfactory simulation performance.

  12. Geo-environmental model for the prediction of potential transmission risk of Dirofilaria in an area with dry climate and extensive irrigated crops. The case of Spain.

    PubMed

    Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando

    2014-03-01

    Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics.

  13. Comparing Broad-Band and Red Edge-Based Spectral Vegetation Indices to Estimate Nitrogen Concentration of Crops Using Casi Data

    NASA Astrophysics Data System (ADS)

    Wang, Yanjie; Liao, Qinhong; Yang, Guijun; Feng, Haikuan; Yang, Xiaodong; Yue, Jibo

    2016-06-01

    In recent decades, many spectral vegetation indices (SVIs) have been proposed to estimate the leaf nitrogen concentration (LNC) of crops. However, most of these indices were based on the field hyperspectral reflectance. To test whether they can be used in aerial remote platform effectively, in this work a comparison of the sensitivity between several broad-band and red edge-based SVIs to LNC is investigated over different crop types. By using data from experimental LNC values over 4 different crop types and image data acquired using the Compact Airborne Spectrographic Imager (CASI) sensor, the extensive dataset allowed us to evaluate broad-band and red edge-based SVIs. The result indicated that NDVI performed the best among the selected SVIs while red edge-based SVIs didn't show the potential for estimating the LNC based on the CASI data due to the spectral resolution. In order to search for the optimal SVIs, the band combination algorithm has been used in this work. The best linear correlation against the experimental LNC dataset was obtained by combining the 626.20nm and 569.00nm wavebands. These wavelengths correspond to the maximal chlorophyll absorption and reflection position region, respectively, and are known to be sensitive to the physiological status of the plant. Then this linear relationship was applied to the CASI image for generating an LNC map, which can guide farmers in the accurate application of their N fertilization strategies.

  14. Drought-related vulnerability and risk assessment of groundwater in Belgium: estimation of the groundwater recharge and crop yield vulnerability with the B-CGMS

    NASA Astrophysics Data System (ADS)

    Jacquemin, Ingrid; Verbeiren, Boud; Vanderhaegen, Sven; Canters, Frank; Vermeiren, Karolien; Engelen, Guy; Huysmans, Marijke; Batelaan, Okke; Tychon, Bernard

    2016-04-01

    Due to common belief that regions under temperate climate are not affected by (meteorological and groundwater) drought, these events and their impacts remain poorly studied: in the GroWaDRISK, we propose to take stock of this question. We aim at providing a better understanding of the influencing factors (land use and land cover changes, water demand and climate) and the drought-related impacts on the environment, water supply and agriculture. The study area is located in the North-East of Belgium, corresponding approximatively to the Dijle and Demer catchments. To establish an overview of the groundwater situation, we assess the system input: the recharge. To achieve this goal, two models, B-CGMS and WetSpass are used to evaluate the recharge, respectively, over agricultural land and over the remaining areas, as a function of climate and for various land uses and land covers. B-CGMS, which is an adapted version for Belgium of the European Crop Growth Monitoring System, is used for assessing water recharge at a daily timestep and under different agricultural lands: arable land (winter wheat, maize...), orchards, horticulture and floriculture and for grassland. B-CGMS is designed to foresee crop yield and obviously it studies the impact of drought on crop yield and raises issues for the potential need of irrigation. For both yields and water requirements, the model proposes a potential mode, driven by temperature and solar radiation, and a water-limited mode for which water availability can limit crop growth. By this way, we can identify where and when water consumption and yield are not optimal, in addition to the Crop Water Stress Index. This index is calculated for a given crop, as the number of days affected by water stress during the growth sensitive period. Both recharge and crop yield are assessed for the current situation (1980 - 2012), taking into account the changing land use/land cover, in terms of areas and localization of the agricultural land and where

  15. Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

    NASA Astrophysics Data System (ADS)

    Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

    2014-12-01

    Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

  16. A reference-based approach for estimating leaf area and cover in the forest herbaceous layer.

    PubMed

    Walter, Christopher A; Burnham, Mark B; Gilliam, Frank S; Peterjohn, William T

    2015-10-01

    Cover data are used to assess vegetative response to a variety of ecological factors. Estimating cover in the herbaceous layer of forests presents a problem because the communities are structurally complex and rich in species. The currently employed techniques for estimating cover are less than optimal for measuring such rich understories because they are inaccurate, slow, or impracticable. A reference-based approach to estimating cover is presented that compares the area of foliar surfaces to the area of an observer's hand. While this technique has been used to estimate cover in prior studies, its accuracy has not been tested. We tested this hand-area method at the individual plant, population, and community scales in a deciduous forest herbaceous layer, and in a separate farm experiment. The precision, accuracy, observer bias, and species bias of the method were tested by comparing the hand-estimated leaf area index values with actual leaf area index, measured using a leaf area meter. The hand-area method was very precise when regressed against actual leaf area index at the plant, population, and community scales (R(2) of 0.97, 0.93, and 0.87). Among the deciduous sites, the hand-area method overestimated leaf area index consistently by 39.1% at all scales. There was no observer bias detected at any scale, but plant overestimation bias was detected in one species at the population scale. The hand-area method is a rapid and reliable technique for estimating leaf area index or cover in the forest herbaceous layer and should be useful to field ecologists interested in answering questions at the plant, population, or community level.

  17. A Crop Simulation System for Integrating Remote Sensing and Climate Information to Reduce Model Uncertainty in Crop Yield Assessments

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Honda, K.; Yui, A.

    2012-12-01

    Uncertainties in crop yield assessments are caused by many factors, including an imperfect model, model parameters and modeling assumptions, as well as errors in data inputs, e.g. climate. Here, we present a crop simulation system that aims to reduce uncertainty in crop yield assessment due to model and data uncertainties. The system uses DSSAT-CSM as the core crop simulation model. The simulation strategy is two-folds: i) crop model parameter estimation and ii) simulation and prediction mode. In i) a noisy Monte Carlo genetic algorithm (NMCGA) is used to estimate crop, soil and management parameters and their uncertainties, where field and remote sensing data can be used in the process. In ii) simulations can be done in an incremental way, where climate data until the current day is used as inputs to the crop model while the climate inputs for rest of the simulation period are generated by a stochastic weather generator based on climatological or climate forecasts information. Also, in the prediction mode, an ensemble Kalman filter (EnKF) can be used to update crop model state variables, e.g., leaf area index (LAI) and soil moisture from remote sensing and field sensors, this can be used in tandem with the climate merging mechanism within the crop simulation system. A case study on wheat modeling in Hokkaido, Japan will be presented. Model uncertainty assessment and implications of the crop simulation system for crop assessment will be discussed.

  18. Economic Analysis of Energy Crop Production in the U.S. - Location, Quantities, Price, and Impacts on Traditional Agricultural Crops

    SciTech Connect

    Walsh, M.E.; De La Torre Ugarte, D.; Slinsky, S.; Graham, R.L.; Shapouri, H.; Ray, D.

    1998-10-04

    POLYSYS is used to estimate US locations where, for any given energy crop price, energy crop production can be economically competitive with conventional crops. POLYSYS is a multi-crop, multi-sector agricultural model developed and maintained by the University of Tennessee and used by the USDA-Economic Research Service. It includes 305 agricultural statistical districts (ASD) which can be aggregated to provide state, regional, and national information. POLYSYS is being modified to include switchgrass, hybrid poplar, and willow on all land suitable for their production. This paper summarizes the preliminary national level results of the POLYSYS analysis for selected energy crop prices for the year 2007 and presents the corresponding maps (for the same prices) of energy crop production locations by ASD. Summarized results include: (1) estimates of energy crop hectares (acres) and quantities (dry Mg, dry tons), (2) identification of traditional crops allocated to energy crop production and calculation of changes in their prices and hectares (acres) of production, and (3) changes in total net farm returns for traditional agricultural crops. The information is useful for identifying areas of the US where large quantities of lowest cost energy crops can most likely be produced.

  19. A thermal-based remote sensing modelling system for estimating crop water use and stress from field to regional scales

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Thermal-infrared remote sensing of land surface temperature provides valuable information for quantifying root-zone water availability, evapotranspiration (ET) and crop condition. A thermal-based scheme, called the Two-Source Energy Balance (TSEB) model, solves for the soil/substrate and canopy temp...

  20. Bayes plus Brass: Estimating Total Fertility for Many Small Areas from Sparse Census Data

    PubMed Central

    Schmertmann, Carl P.; Cavenaghi, Suzana M.; Assunção, Renato M.; Potter, Joseph E.

    2013-01-01

    Small-area fertility estimates are valuable for analysing demographic change, and important for local planning and population projection. In countries lacking complete vital registration, however, small-area estimates are possible only from sparse survey or census data that are potentially unreliable. Such estimation requires new methods for old problems: procedures must be automated if thousands of estimates are required, they must deal with extreme sampling variability in many areas, and they should also incorporate corrections for possible data errors. We present a two-step algorithm for estimating total fertility in such circumstances, and we illustrate by applying the method to 2000 Brazilian Census data for over five thousand municipalities. Our proposed algorithm first smoothes local age-specific rates using Empirical Bayes methods, and then applies a new variant of Brass’s P/F parity correction procedure that is robust under conditions of rapid fertility decline. PMID:24143946

  1. An evaluation of the signature extension approach to large area crop inventories utilizing space image data. [Kansas and North Dakota

    NASA Technical Reports Server (NTRS)

    Nalepka, R. F. (Principal Investigator); Cicone, R. C.; Stinson, J. L.; Balon, R. J.

    1977-01-01

    The author has identified the following significant results. Two examples of haze correction algorithms were tested: CROP-A and XSTAR. The CROP-A was tested in a unitemporal mode on data collected in 1973-74 over ten sample segments in Kansas. Because of the uniformly low level of haze present in these segments, no conclusion could be reached about CROP-A's ability to compensate for haze. It was noted, however, that in some cases CROP-A made serious errors which actually degraded classification performance. The haze correction algorithm XSTAR was tested in a multitemporal mode on 1975-76 LACIE sample segment data over 23 blind sites in Kansas and 18 sample segments in North Dakota, providing wide range of haze levels and other conditions for algorithm evaluation. It was found that this algorithm substantially improved signature extension classification accuracy when a sum-of-likelihoods classifier was used with an alien rejection threshold.

  2. The crop assessment subsystem: System implementation and approaches used for the generation of crop production reports

    NASA Technical Reports Server (NTRS)

    Mcallum, W. E.; Hatch, R. E.; Boatwright, S. M.; Liszcz, C. J.; Evans, S. M. (Principal Investigator)

    1979-01-01

    The primary responsibility of the crop assessment subsystem (CAS) during the three phases of LACIE was to produce crop reports that included estimates of wheat area, yield, and production, as well as a specified set of associated statistical descriptors. The operations of CAS are described with emphasis on sampling strategy, input/output data, evolution of aggregation/reporting system capabilities, and CAS aggregation procedures.

  3. Development of Multi Objective Plan Using Fuzzytechnique for Optimal Cropping Pattern Incommand Area of Aundha Minor Irrigationproject of Maharashtra State (India)

    NASA Astrophysics Data System (ADS)

    Gore, K. P.; Panda, R. K.

    In order to consider the importance of efficient and judicious use of available resources, a case study was undertaken to allocate the land under selected crops in command area of Aundha Minor irrigation project, of Maharashtra State, India so as to maximize the net benefit and production. A linear programming allocation model was formulated by considering the four objectives viz. (i) the maximization of net benefit, (ii) the maximization of total production, (iii) the maximization and minimization of labour employment and (iv) the minimization of investment subject to the constraints dealing with the crops, soil, land, individual crop area, food and nutrient requirement, fertilizer and labour availability, irrigation water release policy, area restriction on individual crops were considered. Irrigation efficiencies of 50, 60 and 70 % were considered, while fertilizer availability was considered at 1.5, 2.0 and 2.5 times of present level along with unlimited availability. Single objective allocation model was developed by using Gam 205 package. Single objective alternate plan was worked out with the constraints of 1.5 times the present fertilizer availability and 60 % irrigation efficiency. The programme was verified by using Lindo package. Multi-objective allocation model was worked out using fuzzy technique to obtain a compromise alternate plan. As a whole compromised solution obtained under multi-objectives plan using fuzzy technique equally helps both the farming community and nation as a whole. In fact, the single objective net benefit optimization gave a benefit to the tune of Rs. 9665 ha-1 y-1, whereas the compromise solution by fuzzy technique gave better return to the tune of Rs. 10278 ha-1 y-1 as against existing benefit of Rs. 4310 ha-1 y-1. Farmers are advised to advocate the optimal cropping pattern obtained by multi-objective allocation model for better return.

  4. Brazil Fire Characterization and Burn Area Estimation Using the Airborne Infrared Disaster Assessment (AIRDAS) System

    NASA Technical Reports Server (NTRS)

    Brass, J. A.; Riggan, P. J.; Ambrosia, V. G.; Lockwood, R. N.; Pereira, J. A.; Higgins, R. G.; Peterson, David L. (Technical Monitor)

    1995-01-01

    Remotely sensed estimations of regional and global emissions from biomass combustion have been used to characterize fire behavior, determine fire intensity, and estimate burn area. Highly temporal, low resolution satellite data have been used to calculate estimates of fire numbers and area burned. These estimates of fire activity and burned area have differed dramatically, resulting in a wide range of predictions on the ecological and environmental impacts of fires. As part of the Brazil/United States Fire Initiative, an aircraft campaign was initiated in 1992 and continued in 1994. This multi-aircraft campaign was designed to assist in the characterization of fire activity, document fire intensity and determine area burned over prescribed, agricultural and wildland fires in the savanna and forests of central Brazil. Using a unique, multispectral scanner (AIRDAS), designed specifically for fire characterization, a variety of fires and burned areas were flown with a high spatial and high thermal resolution scanner. The system was used to measure flame front size, rate of spread, ratio of smoldering to flaming fronts and fire intensity. In addition, long transects were flown to determine the size of burned areas within the cerrado and transitional ecosystems. The authors anticipate that the fire activity and burned area estimates reported here will lead to enhanced information for precise regional trace gas prediction.

  5. A method for estimating the local area damages of superfund waste sites

    SciTech Connect

    Walker, D.R.; Hoehn, J.P. )

    1992-12-01

    A hedonic based interregional wage-rent model is used to estimate the local area damages of Superfund sites. The damages are statistically significant and used to rank the clean up efforts of Superfund sites. The rank depends on total damages, local population, and number of sites located in the area.

  6. Artificial neural network estimation of soil erosion and nutrient concentrations in runoff from land application areas

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The transport of sediment and nutrients from land application areas is an environmental concern. New methods are needed for estimating soil and nutrient concentrations of runoff from cropland areas on which manure is applied. Artificial Neural Networks (ANN) trained with a Backpropagation (BP) algor...

  7. A Methodological Approach to Small Area Estimation for the Behavioral Risk Factor Surveillance System.

    PubMed

    Pierannunzi, Carol; Xu, Fang; Wallace, Robyn C; Garvin, William; Greenlund, Kurt J; Bartoli, William; Ford, Derek; Eke, Paul; Town, G Machell

    2016-07-14

    Public health researchers have used a class of statistical methods to calculate prevalence estimates for small geographic areas with few direct observations. Many researchers have used Behavioral Risk Factor Surveillance System (BRFSS) data as a basis for their models. The aims of this study were to 1) describe a new BRFSS small area estimation (SAE) method and 2) investigate the internal and external validity of the BRFSS SAEs it produced. The BRFSS SAE method uses 4 data sets (the BRFSS, the American Community Survey Public Use Microdata Sample, Nielsen Claritas population totals, and the Missouri Census Geographic Equivalency File) to build a single weighted data set. Our findings indicate that internal and external validity tests were successful across many estimates. The BRFSS SAE method is one of several methods that can be used to produce reliable prevalence estimates in small geographic areas.

  8. A Methodological Approach to Small Area Estimation for the Behavioral Risk Factor Surveillance System

    PubMed Central

    Xu, Fang; Wallace, Robyn C.; Garvin, William; Greenlund, Kurt J.; Bartoli, William; Ford, Derek; Eke, Paul; Town, G. Machell

    2016-01-01

    Public health researchers have used a class of statistical methods to calculate prevalence estimates for small geographic areas with few direct observations. Many researchers have used Behavioral Risk Factor Surveillance System (BRFSS) data as a basis for their models. The aims of this study were to 1) describe a new BRFSS small area estimation (SAE) method and 2) investigate the internal and external validity of the BRFSS SAEs it produced. The BRFSS SAE method uses 4 data sets (the BRFSS, the American Community Survey Public Use Microdata Sample, Nielsen Claritas population totals, and the Missouri Census Geographic Equivalency File) to build a single weighted data set. Our findings indicate that internal and external validity tests were successful across many estimates. The BRFSS SAE method is one of several methods that can be used to produce reliable prevalence estimates in small geographic areas. PMID:27418213

  9. Estimation of minimum oral tract constriction area in sibilant fricatives from aerodynamic data.

    PubMed

    Fujiso, Y; Nozaki, K; Van Hirtum, A

    2015-07-01

    Speech screening of sibilant fricative phonemes is an important tool for oral health care. Nevertheless, screening as a function of quantitative geometrical markers is mostly limited to teeth features whereas the minimum area of the narrowed air passage upstream from the tooth is known to be a key production feature. The minimum area is estimated from non-invasive aerodynamic measurements using a laminar flow model. The influence of viscid flow losses on the area estimation is shown to be negligible. Current data suggest that speech screening is most effective for phoneme /s/, which supports common practice in oral health care.

  10. Error analysis of leaf area estimates made from allometric regression models

    NASA Technical Reports Server (NTRS)

    Feiveson, A. H.; Chhikara, R. S.

    1986-01-01

    Biological net productivity, measured in terms of the change in biomass with time, affects global productivity and the quality of life through biochemical and hydrological cycles and by its effect on the overall energy balance. Estimating leaf area for large ecosystems is one of the more important means of monitoring this productivity. For a particular forest plot, the leaf area is often estimated by a two-stage process. In the first stage, known as dimension analysis, a small number of trees are felled so that their areas can be measured as accurately as possible. These leaf areas are then related to non-destructive, easily-measured features such as bole diameter and tree height, by using a regression model. In the second stage, the non-destructive features are measured for all or for a sample of trees in the plots and then used as input into the regression model to estimate the total leaf area. Because both stages of the estimation process are subject to error, it is difficult to evaluate the accuracy of the final plot leaf area estimates. This paper illustrates how a complete error analysis can be made, using an example from a study made on aspen trees in northern Minnesota. The study was a joint effort by NASA and the University of California at Santa Barbara known as COVER (Characterization of Vegetation with Remote Sensing).

  11. Alcohol co-production from tree crops

    SciTech Connect

    Seibert, M.; Folger, G.; Milne, T.

    1982-06-01

    A concept for the sustainable production of alcohol from fermentable substrates produced on an annual basis by the reproductive organs (pods, fruits, nuts, berries, etc.) of tree crops is presented. The advantages of tree-crop systems include suitability for use on marginal land, potential productivity equivalent to row crops, minimal maintenance and energy-input requirements, environmental compatibility, and the possibility of co-product production. Honeylocust, mesquite, and persimmon are examined as potential US tree-crop species. Other species not previously considered, including osage orange and breadfruit, are suggested as tree-crop candidates for North America and the tropical developing world, respectively. Fermentation of tree-crop organs and the economics of tree-crop systems are also discussed. Currently the greatest area of uncertainty lies in actual pod or fruit yields one can expect from large tree farms under real life conditions. However, ballpark ethanol yield estimates of from 880 to 3470 l hectare/sup -1/ (94 to 400 gal acre/sup -1/) justify further consideration of tree crop systems.

  12. Enhancing The USDA Global Crop Assessment Decision Support System Using Satellite-Based Soil Moisture Estimates Obtained From The Soil Moisture Active Passive Mission

    NASA Astrophysics Data System (ADS)

    Mladenova, I. E.; Bolten, J. D.; Crow, W. T.; Reynolds, C. A.

    2015-12-01

    The primary goal of the U.S. Department of Agriculture Foreign Agricultural Service (FAS) is to provide timely information on current and expected crop supply and demand estimates. Inter-annual variability in crop condition and crop productivity is largely controlled by the amount of available water to the plants. Thus, knowledge of the root-zone soil moisture is critical for the USDA's crop analysts. This information is currently provided by the modified Palmer model (PM). The PM is a two-layer, water balance-based hydrologic model that is driven by daily precipitation and daily minimum and maximum temperature observations based on ground meteorological station measurements from the World Meteorological Organization (WMO) and gridded weather data from the U.S. Air Force 557th Weather Wing (former U.S. Air Force Agency, AFWA). A data assimilation (DA) unit was added to the model to allow the integration of satellite-based soil moisture observations. The DA system was initially developed using retrievals from the Advanced Microwave Scanning Radiometer (AMSR-E), where the AMSR-E soil moisture estimates were ingested into the PM using a 1-D Ensemble Kalman Filter Approach. After the failure of AMSR-E the system was updated and it is currently set to ingest Soil Moisture Ocean Salinity (SMOS)-based retrievals. Operational delivery of the SMOS-based soil moisture product for USDA FAS began in spring, 2014. This talk will demonstrate the added value of assimilating satellite-based data and focus on work that is being done in preparation for updating the system by ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission. Soil moisture estimates derived using data obtained from SMOS and the Advanced Scatterometer (ASCAT) instrument on MetOp have been used as a proxy for the SMAP radiometer and radar products, respectively. The performance of this dual assimilation system would be assessed by examining the lagged rank cross correlation

  13. Bayesian hierarchical models for smoothing in two-phase studies, with application to small area estimation

    PubMed Central

    Ross, Michelle; Wakefield, Jon

    2015-01-01

    Summary Two-phase study designs are appealing since they allow for the oversampling of rare sub-populations which improves efficiency. In this paper we describe a Bayesian hierarchical model for the analysis of two-phase data. Such a model is particularly appealing in a spatial setting in which random effects are introduced to model between-area variability. In such a situation, one may be interested in estimating regression coefficients or, in the context of small area estimation, in reconstructing the population totals by strata. The efficiency gains of the two-phase sampling scheme are compared to standard approaches using 2011 birth data from the research triangle area of North Carolina. We show that the proposed method can overcome small sample difficulties and improve on existing techniques. We conclude that the two-phase design is an attractive approach for small area estimation. PMID:26705382

  14. Large Area Crop Inventory Experiment (LACIE). LACIE phase 1 and phase 2 accuracy assessment. [Kansas, Texas, Minnesota, Montana, and North Dakota

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The author has identified the following significant results. The initial CAS estimates, which were made for each month from April through August, were considerably higher than the USDA/SRS estimates. This was attributed to: (1) the practice of considering bare ground as potential wheat and counting it as wheat; (2) overestimation of the wheat proportions in segments having only a small amount of wheat; and (3) the classification of confusion crops as wheat. At the end of the season most of the segments were reworked using improved methods based on experience gained during the season. In particular, new procedures were developed to solve the three problems listed above. These and other improvements used in the rework experiment resulted in at-harvest estimates that were much closer to the USDA/SRS estimates than those obtained during the regular season.

  15. Estimation of monetary values of air pollutant emissions in various US areas

    SciTech Connect

    Wang, M.Q.; Santini, D.J.

    1994-08-17

    Two general methods of estimating monetary values of air pollutants are presented in this paper. The damage estimate method directly estimated, air pollutant by simulating air quality, identifying health and other welfare impacts damage values and valuing the identified impacts of air pollution, and valuing the identified impacts. Although the method is theoretically sound, many assumptions are involved in each of its estimation steps, and uncertainty exists in each step. The control cost estimate method estimates the marginal emission control cost, which represents the opportunity cost offset by emission reductions from some given control measures. Studies conducted to estimate emission values in US regions used either the damage estimate method or the control cost estimate method. Taking emission values estimated for some US air basins, this paper establishes regression relationships between emission values and total population and air pollutant concentrations. On the basis of the established relationships, both damage-based and control-cost-based emission values are estimated for 17 major US urban areas.

  16. Remote sensing of agricultural crops and soils

    NASA Technical Reports Server (NTRS)

    Bauer, M. E. (Principal Investigator)

    1983-01-01

    Research in the correlative and noncorrelative approaches to image registration and the spectral estimation of corn canopy phytomass and water content is reported. Scene radiation research results discussed include: corn and soybean LANDSAT MSS classification performance as a function of scene characteristics; estimating crop development stages from MSS data; the interception of photosynthetically active radiation in corn and soybean canopies; costs of measuring leaf area index of corn; LANDSAT spectral inputs to crop models including the use of the greenness index to assess crop stress and the evaluation of MSS data for estimating corn and soybean development stages; field research experiment design data acquisition and preprocessing; and Sun-view angles studies of corn and soybean canopies in support of vegetation canopy reflection modeling.

  17. The area-time-integral technique to estimate convective rain volumes over areas applied to satellite data - A preliminary investigation

    NASA Technical Reports Server (NTRS)

    Doneaud, Andre A.; Miller, James R., Jr.; Johnson, L. Ronald; Vonder Haar, Thomas H.; Laybe, Patrick

    1987-01-01

    The use of the area-time-integral (ATI) technique, based only on satellite data, to estimate convective rain volume over a moving target is examined. The technique is based on the correlation between the radar echo area coverage integrated over the lifetime of the storm and the radar estimated rain volume. The processing of the GOES and radar data collected in 1981 is described. The radar and satellite parameters for six convective clusters from storm events occurring on June 12 and July 2, 1981 are analyzed and compared in terms of time steps and cluster lifetimes. Rain volume is calculated by first using the regression analysis to generate the regression equation used to obtain the ATI; the ATI versus rain volume relation is then employed to compute rain volume. The data reveal that the ATI technique using satellite data is applicable to the calculation of rain volume.

  18. Investigation of Aerosol Surface Area Estimation from Number and Mass Concentration Measurements: Particle Density Effect

    PubMed Central

    Ku, Bon Ki; Evans, Douglas E.

    2015-01-01

    For nanoparticles with nonspherical morphologies, e.g., open agglomerates or fibrous particles, it is expected that the actual density of agglomerates may be significantly different from the bulk material density. It is further expected that using the material density may upset the relationship between surface area and mass when a method for estimating aerosol surface area from number and mass concentrations (referred to as “Maynard’s estimation method”) is used. Therefore, it is necessary to quantitatively investigate how much the Maynard’s estimation method depends on particle morphology and density. In this study, aerosol surface area estimated from number and mass concentration measurements was evaluated and compared with values from two reference methods: a method proposed by Lall and Friedlander for agglomerates and a mobility based method for compact nonspherical particles using well-defined polydisperse aerosols with known particle densities. Polydisperse silver aerosol particles were generated by an aerosol generation facility. Generated aerosols had a range of morphologies, count median diameters (CMD) between 25 and 50 nm, and geometric standard deviations (GSD) between 1.5 and 1.8. The surface area estimates from number and mass concentration measurements correlated well with the two reference values when gravimetric mass was used. The aerosol surface area estimates from the Maynard’s estimation method were comparable to the reference method for all particle morphologies within the surface area ratios of 3.31 and 0.19 for assumed GSDs 1.5 and 1.8, respectively, when the bulk material density of silver was used. The difference between the Maynard’s estimation method and surface area measured by the reference method for fractal-like agglomerates decreased from 79% to 23% when the measured effective particle density was used, while the difference for nearly spherical particles decreased from 30% to 24%. The results indicate that the use of

  19. Estimating Small-area Populations by Age and Sex Using Spatial Interpolation and Statistical Inference Methods

    SciTech Connect

    Qai, Qiang; Rushton, Gerald; Bhaduri, Budhendra L; Bright, Eddie A; Coleman, Phil R

    2006-01-01

    The objective of this research is to compute population estimates by age and sex for small areas whose boundaries are different from those for which the population counts were made. In our approach, population surfaces and age-sex proportion surfaces are separately estimated. Age-sex population estimates for small areas and their confidence intervals are then computed using a binomial model with the two surfaces as inputs. The approach was implemented for Iowa using a 90 m resolution population grid (LandScan USA) and U.S. Census 2000 population. Three spatial interpolation methods, the areal weighting (AW) method, the ordinary kriging (OK) method, and a modification of the pycnophylactic method, were used on Census Tract populations to estimate the age-sex proportion surfaces. To verify the model, age-sex population estimates were computed for paired Block Groups that straddled Census Tracts and therefore were spatially misaligned with them. The pycnophylactic method and the OK method were more accurate than the AW method. The approach is general and can be used to estimate subgroup-count types of variables from information in existing administrative areas for custom-defined areas used as the spatial basis of support in other applications.

  20. Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

    NASA Technical Reports Server (NTRS)

    Jasinski, Michael F.; Crago, Richard

    1994-01-01

    Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

  1. An original interpretation of the surface temperature-albedo space to estimate crop evapotranspiration (SEB-1S)

    NASA Astrophysics Data System (ADS)

    Merlin, O.

    2013-05-01

    The space defined by the pair surface temperature (T) and surface albedo (α), and the space defined by the pair T and fractional green vegetation cover (fvg) have been extensively used to estimate evaporative fraction (EF) from optical remote sensing data. In both space-based approaches, evapotranspiration (ET) is estimated as remotely sensed EF times the available energy. For a given data point in the T - α space or in the T - fvg space, EF is derived as the ratio of the distance separating the point from the line identified as the dry edge to the distance separating the dry edge and the line identified as the wet edge. The dry and wet edges are classically defined as the upper and lower limit of the spaces, respectively. When side-by-side investigating the T - α and the T - fvg spaces, one observes that the range covered by T values on the (classically determined) wet edge is different for both spaces. In addition, when extending the wet and dry lines of the T - α space, both lines cross at α ≈ 0.4 although the wet and dry edges of the T - fvg space never cross for 0 ≤ fvg < 1. In this paper, a new ET (EF) model (SEB-1S) is derived by revisiting the classical physical interpretation of the T - α space to make its wet edge consistent with that of the T - fvg space. SEB-1S is tested over a 16 km by 10 km irrigated area in northwestern Mexico during the 2007-2008 agricultural season. The classical T - α space-based model is implemented as benchmark to evaluate the performance of SEB-1S. Input data are composed of ASTER (Advanced Spaceborne Thermal Emission and Reflection radiometer) thermal infrared, Formosat-2 shortwave, and station-based meteorological data. The fluxes simulated by SEB-1S and the classical T - α space-based model are compared on seven ASTER overpass dates with the in situ measurements collected at six locations within the study domain. The ET simulated by SEB-1S is significantly more accurate and robust than that predicted by the

  2. Accounting for unsearched areas in estimating wind turbine-caused fatality

    USGS Publications Warehouse

    Huso, Manuela M.P.; Dalthorp, Dan

    2014-01-01

    With wind energy production expanding rapidly, concerns about turbine-induced bird and bat fatality have grown and the demand for accurate estimation of fatality is increasing. Estimation typically involves counting carcasses observed below turbines and adjusting counts by estimated detection probabilities. Three primary sources of imperfect detection are 1) carcasses fall into unsearched areas, 2) carcasses are removed or destroyed before sampling, and 3) carcasses present in the searched area are missed by observers. Search plots large enough to comprise 100% of turbine-induced fatality are expensive to search and may nonetheless contain areas unsearchable because of dangerous terrain or impenetrable brush. We evaluated models relating carcass density to distance from the turbine to estimate the proportion of carcasses expected to fall in searched areas and evaluated the statistical cost of restricting searches to areas near turbines where carcass density is highest and search conditions optimal. We compared 5 estimators differing in assumptions about the relationship of carcass density to distance from the turbine. We tested them on 6 different carcass dispersion scenarios at each of 3 sites under 2 different search regimes. We found that even simple distance-based carcass-density models were more effective at reducing bias than was a 5-fold expansion of the search area. Estimators incorporating fitted rather than assumed models were least biased, even under restricted searches. Accurate estimates of fatality at wind-power facilities will allow critical comparisons of rates among turbines, sites, and regions and contribute to our understanding of the potential environmental impact of this technology.

  3. MODELING WORLD BIOENERGY CROP POTENTIAL

    NASA Astrophysics Data System (ADS)

    Hagiwara, Kensuke; Hanasaki, Naota; Kanae, Shinjiro

    Bioenergy is regarded as clean energy due to its characteristics and expected to be a new support of world energy de¬mand, but there are few integrated assessments of the potential of bioenergy considering sustainable land use. We esti¬mated the global bioenergy potential with an integrated global water resources model, the H08. It can simulate the crop yields on global-scale at a spatial resolution of 0.50.5. Seven major crops in the world were considered; namely, maize, sugar beet, sugar cane, soybean, rapeseed, rice, and wheat, of which the first 5 are commonly used to produce biofuel now. Three different land-cover types were chosen as potential area for cultivation of biofuel-producing crop: fallow land, grassland, and portion of forests (excluding areas sensitive for biodiversity such as frontier forest). We attempted to estimate the maximum global bioenergy potential and it was estimated to be 1120EJ. Bioenergy potential depends on land-use limitations for the protection of bio-diversity and security of food. In another condition which assumed more land-use limitations, bioenergy potential was estimated to be 70-233EJ.

  4. Forensic dental age estimation by measuring root dentin translucency area using a new digital technique.

    PubMed

    Acharya, Ashith B

    2014-05-01

    Dentin translucency measurement is an easy yet relatively accurate approach to postmortem age estimation. Translucency area represents a two-dimensional change and may reflect age variations better than length. Manually measuring area is challenging and this paper proposes a new digital method using commercially available computer hardware and software. Area and length were measured on 100 tooth sections (age range, 19-82 years) of 250 μm thickness. Regression analysis revealed lower standard error of estimate and higher correlation with age for length than for area (R = 0.62 vs. 0.60). However, test of regression formulae on a control sample (n = 33, 21-85 years) showed smaller mean absolute difference (8.3 vs. 8.8 years) and greater frequency of smaller errors (73% vs. 67% age estimates ≤ ± 10 years) for area than for length. These suggest that digital area measurements of root translucency may be used as an alternative to length in forensic age estimation.

  5. Large Area Crop Inventory Experiment (LACIE). Detecting and monitoring agricultural vegetative water stress over large areas using LANDSAT digital data. [Great Plains

    NASA Technical Reports Server (NTRS)

    Thompson, D. R.; Wehmanen, O. A. (Principal Investigator)

    1978-01-01

    The author has identified the following significant results. The Green Number Index technique which uses LANDSAT digital data from 5X6 nautical mile sampling frames was expanded to evaluate its usefulness in detecting and monitoring vegetative water stress over the Great Plains. At known growth stages for wheat, segments were classified as drought or non drought. Good agreement was found between the 18 day remotely sensed data and a weekly ground-based crop moisture index. Operational monitoring of the 1977 U.S.S.R. and Australian wheat crops indicated drought conditions. Drought isoline maps produced by the Green Number Index technique were in good agreement with conventional sources.

  6. Revised stratigraphy of Area 123, Koobi Fora, Kenya, and new age estimates of its fossil mammals, including hominins.

    PubMed

    Gathogo, Patrick N; Brown, Francis H

    2006-11-01

    Recent geologic study shows that all hominins and nearly all other published mammalian fossils from Paleontological Collection Area 123, Koobi Fora, Kenya, derive from levels between the KBS Tuff (1.87+/-0.02 Ma) and the Lower Ileret Tuff (1.53+/-0.01 Ma). More specifically, the fossils derive from 53 m of section below the Lower Ileret Tuff, an interval in which beds vary markedly laterally, especially those units containing molluscs and algal stromatolites. The upper Burgi Member (approximately 2.00-1.87 Ma) crops out only in the southwestern part of Area 123. Adjacent Area 110 contains larger exposures of the member, and there the KBS Tuff is preserved as an airfall ash in lacustrine deposits and also as a fluvially redeposited ash. We observed no mammalian fossils in situ in this member in Area 123, but surface specimens have been documented in some monographic treatments. Fossil hominins from Area 123 were attributed to strata above the KBS Tuff in the 1970s, but later they were assigned to strata below the KBS Tuff (now called the upper Burgi Member). This study definitively places the Area 123 hominins in the KBS Member. Most of these hominins are between 1.60 and 1.65 myr in age, but the youngest may date to only 1.53 Ma, and the oldest, to 1.75 Ma. All are 0.15-0.30 myr younger than previously estimated. The new age estimates, in conjunction with published taxonomic attributions of fossils, suggest that at least two species of Homo coexisted in the region along with A. boisei until at least 1.65 Ma. Comparison of crania KNM-ER 1813 and KNM-ER 1470, which were believed to be of comparable age, is at the focus of the debate over whether Homo habilis sensu lato is in fact composed of two species: Homo habilis and Homo rudolfensis. These two crania are separated in time by approximately 0.25 myr, and therefore, arguments for their conspecificity no longer need to confront the issue of unusually high contemporaneous variation within a single species. PMID

  7. Hailfall: the relationship between radar measurements and crop damage

    NASA Astrophysics Data System (ADS)

    Schiesser, H. H.

    Relationships between a radar-derived hail intensity parameter, "kinetic energy aloft", and hail damage to crops on the ground are presented. Several factors influence such a relations: the drift of the hailstones in the downdrafts, the type of crop and the stage of maturity of a single crop. The damage functions were derived utilizing data from a severe hailstorm, which occurred during the hail suppression experiment Grossversuch IV in Switzerland. They permit conversion of radar measurements into estimates of expected amount and area of hail damage for nine different crops at various stages of maturity. The achieved estimates can be used for damage exceeding 20%. In the future this information could be available immediately after a storm passes over a radar observation area and could help to satisfy the increasing demand for severe-weather data to judge the risk of hail damage in endangered areas.

  8. Estimation of the sugar cane cultivated area from LANDSAT images using the two phase sampling method

    NASA Technical Reports Server (NTRS)

    Parada, N. D. J. (Principal Investigator); Cappelletti, C. A.; Mendonca, F. J.; Lee, D. C. L.; Shimabukuro, Y. E.

    1982-01-01

    A two phase sampling method and the optimal sampling segment dimensions for the estimation of sugar cane cultivated area were developed. This technique employs visual interpretations of LANDSAT images and panchromatic aerial photographs considered as the ground truth. The estimates, as a mean value of 100 simulated samples, represent 99.3% of the true value with a CV of approximately 1%; the relative efficiency of the two phase design was 157% when compared with a one phase aerial photographs sample.

  9. Estimation of Leaf Area Index and Plant Area Index of a Submerged Macrophyte Canopy Using Digital Photography

    PubMed Central

    Zhao, Dehua; Xie, Dong; Zhou, Hengjie; Jiang, Hao; An, Shuqing

    2012-01-01

    Non-destructive estimation using digital cameras is a common approach for estimating leaf area index (LAI) of terrestrial vegetation. However, no attempt has been made so far to develop non-destructive approaches to LAI estimation for aquatic vegetation. Using the submerged plant species Potamogeton malainus, the objective of this study was to determine whether the gap fraction derived from vertical photographs could be used to estimate LAI of aquatic vegetation. Our results suggested that upward-oriented photographs taken from beneath the water surface were more suitable for distinguishing vegetation from other objects than were downward-oriented photographs taken from above the water surface. Exposure settings had a substantial influence on the identification of vegetation in upward-oriented photographs. Automatic exposure performed nearly as well as the optimal trial exposure, making it a good choice for operational convenience. Similar to terrestrial vegetation, our results suggested that photographs taken for the purpose of distinguishing gap fraction in aquatic vegetation should be taken under diffuse light conditions. Significant logarithmic relationships were observed between the vertical gap fraction derived from upward-oriented photographs and plant area index (PAI) and LAI derived from destructive harvesting. The model we developed to depict the relationship between PAI and gap fraction was similar to the modified theoretical Poisson model, with coefficients of 1.82 and 1.90 for our model and the theoretical model, respectively. This suggests that vertical upward-oriented photographs taken from below the water surface are a feasible alternative to destructive harvesting for estimating PAI and LAI for the submerged aquatic plant Potamogeton malainus. PMID:23226557

  10. Innovative LIDAR 3D Dynamic Measurement System to estimate fruit-tree leaf area.

    PubMed

    Sanz-Cortiella, Ricardo; Llorens-Calveras, Jordi; Escolà, Alexandre; Arnó-Satorra, Jaume; Ribes-Dasi, Manel; Masip-Vilalta, Joan; Camp, Ferran; Gràcia-Aguilá, Felip; Solanelles-Batlle, Francesc; Planas-DeMartí, Santiago; Pallejà-Cabré, Tomàs; Palacin-Roca, Jordi; Gregorio-Lopez, Eduard; Del-Moral-Martínez, Ignacio; Rosell-Polo, Joan R

    2011-01-01

    In this work, a LIDAR-based 3D Dynamic Measurement System is presented and evaluated for the geometric characterization of tree crops. Using this measurement system, trees were scanned from two opposing sides to obtain two three-dimensional point clouds. After registration of the point clouds, a simple and easily obtainable parameter is the number of impacts received by the scanned vegetation. The work in this study is based on the hypothesis of the existence of a linear relationship between the number of impacts of the LIDAR sensor laser beam on the vegetation and the tree leaf area. Tests performed under laboratory conditions using an ornamental tree and, subsequently, in a pear tree orchard demonstrate the correct operation of the measurement system presented in this paper. The results from both the laboratory and field tests confirm the initial hypothesis and the 3D Dynamic Measurement System is validated in field operation. This opens the door to new lines of research centred on the geometric characterization of tree crops in the field of agriculture and, more specifically, in precision fruit growing.

  11. Innovative LIDAR 3D Dynamic Measurement System to estimate fruit-tree leaf area.

    PubMed

    Sanz-Cortiella, Ricardo; Llorens-Calveras, Jordi; Escolà, Alexandre; Arnó-Satorra, Jaume; Ribes-Dasi, Manel; Masip-Vilalta, Joan; Camp, Ferran; Gràcia-Aguilá, Felip; Solanelles-Batlle, Francesc; Planas-DeMartí, Santiago; Pallejà-Cabré, Tomàs; Palacin-Roca, Jordi; Gregorio-Lopez, Eduard; Del-Moral-Martínez, Ignacio; Rosell-Polo, Joan R

    2011-01-01

    In this work, a LIDAR-based 3D Dynamic Measurement System is presented and evaluated for the geometric characterization of tree crops. Using this measurement system, trees were scanned from two opposing sides to obtain two three-dimensional point clouds. After registration of the point clouds, a simple and easily obtainable parameter is the number of impacts received by the scanned vegetation. The work in this study is based on the hypothesis of the existence of a linear relationship between the number of impacts of the LIDAR sensor laser beam on the vegetation and the tree leaf area. Tests performed under laboratory conditions using an ornamental tree and, subsequently, in a pear tree orchard demonstrate the correct operation of the measurement system presented in this paper. The results from both the laboratory and field tests confirm the initial hypothesis and the 3D Dynamic Measurement System is validated in field operation. This opens the door to new lines of research centred on the geometric characterization of tree crops in the field of agriculture and, more specifically, in precision fruit growing. PMID:22163926

  12. The Impact of the Species–Area Relationship on Estimates of Paleodiversity

    PubMed Central

    2005-01-01

    Estimates of paleodiversity patterns through time have relied on datasets that lump taxonomic occurrences from geographic areas of varying size per interval of time. In essence, such estimates assume that the species–area effect, whereby more species are recorded from larger geographic areas, is negligible for fossil data. We tested this assumption by using the newly developed Miocene Mammal Mapping Project database of western North American fossil mammals and its associated analysis tools to empirically determine the geographic area that contributed to species diversity counts in successive temporal bins. The results indicate that a species–area effect markedly influences counts of fossil species, just as variable spatial sampling influences diversity counts on the modern landscape. Removing this bias suggests some traditionally recognized peaks in paleodiversity are just artifacts of the species–area effect while others stand out as meriting further attention. This discovery means that there is great potential for refining existing time-series estimates of paleodiversity, and for using species–area relationships to more reliably understand the magnitude and timing of such biotically important events as extinction, lineage diversification, and long-term trends in ecological structure. PMID:16004509

  13. Improving global fire carbon emissions estimates by combining moderate resolution burned area and active fire observations

    NASA Astrophysics Data System (ADS)

    Randerson, J. T.; Chen, Y.; Giglio, L.; Rogers, B. M.; van der Werf, G.

    2011-12-01

    In several important biomes, including croplands and tropical forests, many small fires exist that have sizes that are well below the detection limit for the current generation of burned area products derived from moderate resolution spectroradiometers. These fires likely have important effects on greenhouse gas and aerosol emissions and regional air quality. Here we developed an approach for combining 1km thermal anomalies (active fires; MOD14A2) and 500m burned area observations (MCD64A1) to estimate the prevalence of these fires and their likely contribution to burned area and carbon emissions. We first estimated active fires within and outside of 500m burn scars in 0.5 degree grid cells during 2001-2010 for which MCD64A1 burned area observations were available. For these two sets of active fires we then examined mean fire radiative power (FRP) and changes in enhanced vegetation index (EVI) derived from 16-day intervals immediately before and after each active fire observation. To estimate the burned area associated with sub-500m fires, we first applied burned area to active fire ratios derived solely from within burned area perimeters to active fires outside of burn perimeters. In a second step, we further modified our sub-500m burned area estimates using EVI changes from active fires outside and within of burned areas (after subtracting EVI changes derived from control regions). We found that in northern and southern Africa savanna regions and in Central and South America dry forest regions, the number of active fires outside of MCD64A1 burned areas increased considerably towards the end of the fire season. EVI changes for active fires outside of burn perimeters were, on average, considerably smaller than EVI changes associated with active fires inside burn scars, providing evidence for burn scars that were substantially smaller than the 25 ha area of a single 500m pixel. FRP estimates also were lower for active fires outside of burn perimeters. In our

  14. Rice crop risk map in Babahoyo canton (Ecuador)

    NASA Astrophysics Data System (ADS)

    Valverde Arias, Omar; Tarquis, Ana; Garrido, Alberto

    2016-04-01

    determinate which level of rice crop requirement is met. Finally we have established rice crop zones classified as: suitable, moderate suitable, marginal suitable and unsuitable. Several methods have been used to estimate the degree with which crop requirements are satisfied, pondering weights of limiting factors to adequate crop conditions. Better conditions for cropping in a specific area imply less risk in production. In this case, crop will be less affected by pests and disease, although this closely depends on crop management. Farmers have to invest less money to produce and could increase their benefit. Results are showed and discussed with the aim to study the efficiency and potential of this risk map.

  15. Historical tank content estimate for the southeast quadrant of the Hanford 200 area

    SciTech Connect

    Brevick, C.H.; Stroup, J.L.; Funk, J.W., Fluor Daniel Hanford

    1997-03-14

    The Historical Tank Content Estimate for the Quadrant provides historical information on a tank-by-tank basis of the radioactive mixed wastes stored in the underground single-shell tanks for the Hanford 200 Areas. This report summarized historical information such as waste history, level history, temperature history, riser configuration, tank integrity, and inventory estimates on a tank- by-tank basis. Tank farm aerial photographs and interior tank montages are also provided for each tank. A description of the development of data for the document of the inventory estimates provided by Los Alamos National Laboratory are also given in this report.

  16. Historical tank content estimate for the northwest quadrant ofthe Hanford 200 west area

    SciTech Connect

    Brevick, C.H.; Stroup, J.L.; Funk, J.W., Fluor Daniel Hanford

    1997-03-06

    The Historical Tank Content Estimate for the Quadrant provides historical information on a tank-by-tank basis of the radioactive mixed wastes stored in the underground single-shell tanks for the Hanford 200 West Area. This report summarized historical information such as waste history, level history, temperature history, riser configuration, tank integrity, and inventory estimates on a tank-by-tank basis. Tank farm aerial photographs and interior tank montages are also provided for each tank. A description of the development of data for the document of the inventory estimates provided by Los Alamos National Labo1368ratory are also given in this report.

  17. Historical tank content estimate for the southwest quadrant of the Hanford 200 west area

    SciTech Connect

    Brevick, C.H.; Stroup, J.L.; Funk, J.W., Fluor Daniel Hanford

    1997-03-06

    The Historical Tank Content Estimate for the Quadrant provides historical information on a tank-by-tank basis of the radioactive mixed wastes stored in the underground single-shell tanks for the Hanford 200 West Area. This report summarized historical information such as waste history, level history, temperature history, riser configuration, tank integrity, and inventory estimates on a tank- by-tank basis. Tank farm aerial photographs and interior tank montages are also provided for each tank. A description of the development of data for the document of the inventory estimates provided by Los Alamos National Laboratory are also given in this report.

  18. Methods used in estimating the ground water supply in the Wichita, Kansas well-field area

    USGS Publications Warehouse

    Williams, C.C.; Lohman, S.W.

    1947-01-01

    This paper presents the methods used in studying the groundwater hydrology of an area in Harvey and Sedgwick Counties, Kansas, from which the city of Wichita derives its water supply. A summary of the data available for study is presented and several hydrologic factors are evaluated. The relationship between groundwater levels and precipitation is shown, and recharge is estimated. The effect of pumping on water levels is shown graphically, and the quantity of water withdrawn from storage is estimated from several water-table contour maps. The data are analyzed and the quantity of water available for pumping is estimated.

  19. Estimation of land surface evaporation map over large areas using remote sensing data

    NASA Astrophysics Data System (ADS)

    Jiang, Le

    Accurate estimation of surface energy fluxes is essential for various hydrological, meteorological, agricultural and ecological applications. Over the years, a wide variety of instrument systems and estimation methodologies have been developed to measure and estimate surface fluxes. In this study, a simple scheme is proposed to estimate surface evaporation over large heterogeneous areas using remote sensing data. This approach is based on an extension of the Priestley-Taylor equation and a relationship between remotely sensed surface temperature and vegetation index. Further simplification by using more generalized form for remotely sensed surface parameters set leads to a simpler formulation for evaporative fraction within a trapezoid/triangle space of remotely sensed vegetation index and surface temperature parameter space. Compared to ground flux observations by the Atmospheric Radiation Measurement (ARM) program, six case studies varying from early spring to late summer over the central United States show that the proposed method provides better estimation accuracy for surface evaporation than the original Priestley-Taylor method. Detailed comparison with the widely used aerodynamic resistance energy balance residual method suggests that the proposed method can achieve similar or better estimation of latent heat flux over large areas with much less input parameters. The residual method, on the other hand, requires estimation of aerodynamic resistance to heat transfer that necessitates the measurements of several ground-based observations including land surface vegetation height and surface wind.

  20. Quantifying the impact of changes in crop area on evapotranspiration regimes in the US corn and soybean belts through phenological modeling and data assimilation

    NASA Astrophysics Data System (ADS)

    Kovalskyy, V.; Henebry, G. M.

    2010-12-01

    In recent years, fluctuations in food, feed, and fuel prices have led to shifts in the area of cropland dedicated to maize and soybean cultivation in the Northern Great Plains. We report here on a modeling experiment that compares three different simulated scenarios for actual evapotranspiration (ETa) from maize-soybean dominated areas in North Dakota, South Dakota, Nebraska, Iowa, and Minnesota during the 2000-2009 growing seasons. Scenario 1 relies on MODIS-derived crop maps to provide a baseline of subpixel crop proportions; Scenario 2 increases the proportion of maize by to 100 percent; Scenario 3 substitutes grassland for half the maize. We use a simple soil water balance model of ETa linked to an empirically derived crop specific phenology model also capable of producing seasonal trajectories of canopy attributes. This coupled model has been successfully deployed using flux tower records from multiple locations in the central US. Forcing the coupled model using data from NLDAS, we derive seasonal trajectories of daily NDVI and ETa as well as phenological transition points for maize, soybean, and grassland for each scenario. Seasonal differences in ETa among the three scenarios underscore the importance of how land use modulates land surface phenologies and, in turn, water and energy balances.

  1. Biosolids, soil, crop, ground-water, and streambed-sediment data for a biosolids-application area near Deer Trail, Colorado, 2002-2003

    USGS Publications Warehouse

    Yager, Tracy J.B.; Smith, David B.; Crock, James G.

    2004-01-01

    In January 1999, the U.S. Geological Survey began an expanded monitoring program near Deer Trail, Colorado, in cooperation with the Metro Wastewater Reclamation District and the North Kiowa Bijou Groundwater Management District. Monitoring components were biosolids, soils, crops, ground water, and streambed sediments. The monitoring program addresses concerns from the public about chemical effects from applications of biosolids to farmland in the Deer Trail, Colorado, area. Constituents of primary concern to the public are arsenic, cadmium, copper, lead, mercury, molybdenum, nickel, selenium, zinc, plutonium, and gross alpha and gross beta activity, and they are included for all monitoring components. This report presents chemical data from the fourth and fifth years of the monitoring program, 2002 through 2003, for biosolids, soils, crops, alluvial and bedrock ground water, and streambed sediment. The ground-water section also includes climate data and water levels. The chemical data include the constituents of highest concern to the public in addition to many other constituents.

  2. Estimating Radiological Doses to Predators Foraging in a Low-Level Radioactive Waste Management Area

    SciTech Connect

    L.Soholt; G.Gonzales; P.Fresquez; K.Bennett; E.Lopez

    2003-03-01

    Since 1957, Los Alamos National Laboratory has operated Area G as its low-level, solid radioactive waste management and disposal area. Although the waste management area is developed, plants, small mammals, and avian and mammalian predators still occupy the less disturbed and revegetated portions of the land. For almost a decade, we have monitored the concentrations of selected radionuclides in soils, plants, and small mammals at Area G. The radionuclides tritium, plutonium-238, and plutonium-239 are regularly found at levels above regional background in all three media. Based on radionuclide concentrations in mice collected from 1994 to 1999, we calculated doses to higher trophic levels (owl, hawk, kestrel, and coyote) that forage on the waste management area. These predators play important functions in the regional ecosystems and are an important part of local Native American traditional tales that identify the uniqueness of their culture. The estimated doses are compared to Department of Energy's interim limit of 0.1 rad/day for the protection of terrestrial wildlife. We used exposure parameters that were derived from the literature for each receptor, including Environmental Protection Agency's exposure factors handbook. Estimated doses to predators ranged from 9E-06 to 2E-04 rad/day, assuming that they forage entirely on the waste management area. These doses are greater than those calculated for predators foraging exclusively in reference areas, but are still well below the interim dose limit. We believe that these calculated doses represent upper-bound estimates of exposure for local predators because the larger predators forage over areas that are much greater than the 63-acre waste management area. Based on these results, we concluded that predators foraging on this area do not face a hazard from radiological exposure under current site conditions.

  3. Fire Emissions Estimates in Siberia: Evaluation of Uncertainties in Area Burned, Land Cover, and Fuel Consumption

    NASA Astrophysics Data System (ADS)

    Kukavskaya, E.; Soja, A. J.; Ivanova, G. A.; Petkov, A.; Ponomarev, E. I.; Conard, S. G.

    2012-12-01

    Wildfire is one of the main disturbance factors in the boreal zone of Russia. Fires in the Russian boreal forest range from low-severity surface fires to high-severity crown fires. Estimates of carbon emissions from fires in Russia vary substantially due to differences in ecosystem classification and mapping, burned area calculations, and estimates of fuel consumption. We examined uncertainties in different parameters used to estimate biomass burning emissions. Several fire datasets (Institute of Forest burned area product, MCD45, MCD64, MOD14/MYD14, official data) were compared to estimate uncertainties in area burned in Siberia. Area burned was found to differ significantly by data source, with satellite data being by an order of magnitude greater than ground-based data. Differences between mapped ecosystems were also compared and contrasted on the basis of five land cover maps (GLC-2000, Globcover-2009, MODIS Collection 4 and 5 Global Land Cover, and the Digitized Ecosystem map of the Former Soviet Union) to evaluate the potential for error resulting from disparate vegetation structure and fuel consumption estimates. The examination of land cover maps showed that estimates of relative proportion of fire by ecosystem type varied substantially for the same year from map to map. Fuel consumption remains one of the main uncertainties in estimates of biomass burning emissions in Siberia. Accurate fuel consumption estimates are obtained in the course of fire experiments with pre- and post-fire biomass measuring. Our large-scale experiments carried out in the course of the FIRE BEAR (Fire Effects in the Boreal Eurasia Region) Project provided quantitative and qualitative data on ecosystem state and carbon emissions due to fires of known behavior in major forest types of Siberia that could be used to verify large-scale carbon emissions estimates. Global climate change is expected to result in increase of fire hazard and area burned, leading to impacts on global air

  4. The use of large-area spectral data in wheat yield estimation

    NASA Technical Reports Server (NTRS)

    Barnett, T. L.; Thompson, D. R.

    1982-01-01

    Large-area relations between satellite spectral data and end-of-season crop yield were investigated. Green Index Number (GIN) values from Landsat MSS data of sample segments throughout the U.S. Great Plains winter wheat belt in 1978 were correlated to county USDA-SRS reported yields. A linear relation between GIN and yield appeared to exist up to GIN values of 40 or 50, covering cases of severe to moderate stress. In a test on 1978 Texas winter wheat at the county level, GIN values for sample segments in the counties were used in conjunction with an agronomic-meteorological yield model. The combined fit explained significantly more of the observed yield variation at the county level than the agromet model alone.

  5. [Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite].

    PubMed

    Yu, Chao; Chen, Liang-fu; Li, Shen-shen; Tao, Jin-hua; Su, Lin

    2015-03-01

    Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the

  6. [Estimating Biomass Burned Areas from Multispectral Dataset Detected by Multiple-Satellite].

    PubMed

    Yu, Chao; Chen, Liang-fu; Li, Shen-shen; Tao, Jin-hua; Su, Lin

    2015-03-01

    Biomass burning makes up an important part of both trace gases and particulate matter emissions, which can efficiently degrade air quality and reduce visibility, destabilize the global climate system at regional to global scales. Burned area is one of the primary parameters necessary to estimate emissions, and considered to be the largest source of error in the emission inventory. Satellite-based fire observations can offer a reliable source of fire occurrence data on regional and global scales, a variety of sensors have been used to detect and map fires in two general approaches: burn scar mapping and active fire detection. However, both of the two approaches have limitations. In this article, we explore the relationship between hotspot data and burned area for the Southeastern United States, where a significant amount of biomass burnings from both prescribed and wild fire took place. MODIS (Moderate resolution imaging spectrometer) data, which has high temporal-resolution, can be used to monitor ground biomass. burning in time and provided hot spot data in this study. However, pixel size of MODIS hot spot can't stand for the real ground burned area. Through analysis of the variation of vegetation band reflectance between pre- and post-burn, we extracted the burned area from Landsat-5 TM (Thematic Mapper) images by using the differential normalized burn ratio (dNBR) which is based on TM band4 (0.84 μm) and TM band 7(2.22 μm) data. We combined MODIS fire hot spot data and Landsat-5 TM burned scars data to build the burned area estimation model, results showed that the linear correlation coefficient is 0.63 and the relationships vary as a function of vegetation cover. Based on the National Land Cover Database (NLCD), we built burned area estimation model over different vegetation cover, and got effective burned area per fire pixel, values for forest, grassland, shrub, cropland and wetland are 0.69, 1.27, 0.86, 0.72 and 0.94 km2 respectively. We validated the

  7. Large Area Crop Inventory Experiment (LACIE). First interim phase 3 evaluation report. [Great Plains and U.S.S.R.

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The author has identified the following significant results. LACIE acreage estimates were in close agreement with SRS estimates, and an operational system with a 14 day LANDSAT data turnaround could have produced an accurate acreage estimate (one which satisfied the 90/90 criterion) 1 1/2 to 2 months before harvest. Low yield estimates, resulting from agromet conditions not taken into account in the yield models, caused production estimates to be correspondingly low. However, both yield and production estimates satisfied the LACIE 90/90 criterion for winter wheat in the yardstick region.

  8. Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality

    PubMed Central

    Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel

    2016-01-01

    Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991–2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA). PMID:27468328

  9. Area Estimation of Deep-Sea Surfaces from Oblique Still Images

    PubMed Central

    Souto, Miguel; Afonso, Andreia; Calado, António; Madureira, Pedro; Campos, Aldino

    2015-01-01

    Estimating the area of seabed surfaces from pictures or videos is an important problem in seafloor surveys. This task is complex to achieve with moving platforms such as submersibles, towed or remotely operated vehicles (ROV), where the recording camera is typically not static and provides an oblique view of the seafloor. A new method for obtaining seabed surface area estimates is presented here, using the classical set up of two laser devices fixed to the ROV frame projecting two parallel lines over the seabed. By combining lengths measured directly from the image containing the laser lines, the area of seabed surfaces is estimated, as well as the camera’s distance to the seabed, pan and tilt angles. The only parameters required are the distance between the parallel laser lines and the camera’s horizontal and vertical angles of view. The method was validated with a controlled in situ experiment using a deep-sea ROV, yielding an area estimate error of 1.5%. Further applications and generalizations of the method are discussed, with emphasis on deep-sea applications. PMID:26177287

  10. Footprint (A Screening Model for Estimating the Area of a Plume Produced from Gasoline Containing Ethanol

    EPA Science Inventory

    FOOTPRINT is a simple and user-friendly screening model to estimate the length and surface area of BTEX plumes in ground water produced from a spill of gasoline that contains ethanol. Ethanol has a potential negative impact on the natural biodegradation of BTEX compounds in groun...

  11. Area Estimation of Deep-Sea Surfaces from Oblique Still Images.

    PubMed

    Dias, Frederico Carvalho; Gomes-Pereira, José; Tojeira, Inês; Souto, Miguel; Afonso, Andreia; Calado, António; Madureira, Pedro; Campos, Aldino

    2015-01-01

    Estimating the area of seabed surfaces from pictures or videos is an important problem in seafloor surveys. This task is complex to achieve with moving platforms such as submersibles, towed or remotely operated vehicles (ROV), where the recording camera is typically not static and provides an oblique view of the seafloor. A new method for obtaining seabed surface area estimates is presented here, using the classical set up of two laser devices fixed to the ROV frame projecting two parallel lines over the seabed. By combining lengths measured directly from the image containing the laser lines, the area of seabed surfaces is estimated, as well as the camera's distance to the seabed, pan and tilt angles. The only parameters required are the distance between the parallel laser lines and the camera's horizontal and vertical angles of view. The method was validated with a controlled in situ experiment using a deep-sea ROV, yielding an area estimate error of 1.5%. Further applications and generalizations of the method are discussed, with emphasis on deep-sea applications. PMID:26177287

  12. Wheat cultivation: Identifying and estimating area by means of LANDSAT data

    NASA Technical Reports Server (NTRS)

    Dejesusparada, N. (Principal Investigator); Mendonca, F. J.; Cottrell, D. A.; Tardin, A. T.; Lee, D. C. L.; Shimabukuro, Y. E.; Moreira, M. A.; Delima, A. M.; Maia, F. C. S.

    1981-01-01

    Automatic classification of LANDSAT data supported by aerial photography for identification and estimation of wheat growing areas was evaluated. Data covering three regions in the State of Rio Grande do Sul, Brazil were analyzed. The average correct classification of IMAGE-100 data was 51.02% and 63.30%, respectively, for the periods of July and of September/October, 1979.

  13. ACCURACY OF THE 1992 NATIONAL LAND COVER DATASET AREA ESTIMATES: AN ANALYSIS AT MULTIPLE SPATIAL EXTENTS

    EPA Science Inventory

    Abstract for poster presentation:

    Site-specific accuracy assessments evaluate fine-scale accuracy of land-use/land-cover(LULC) datasets but provide little insight into accuracy of area estimates of LULC

    classes derived from sampling units of varying size. Additiona...

  14. Improved leaf area index based biomass estimations for Zostera marina L.

    PubMed

    Solana-Arellano, Elena; Echavarria-Heras, Hector; Gallegos Martinez, Margarita

    2003-12-01

    The application of special scanning technologies in plant population studies makes it now possible to offer reliable indirect estimations of Leaf Area Index (LAI). This has stimulated the adaptation of related biomass assessment methods and has provided a way to simplify tedious laboratory procedures whilst avoiding destructive sampling. Particularly, above-ground biomass for Zostera marina L. has been expressed depending linearly on Leaf Area Index. Nevertheless, we demonstrate that this approach produces biased estimations. It is also shown that expressing leaf dry weight by means of an allometric function of length and width can eliminate bias. Furthermore, the dominant term of the associated power series expansion becomes the aforementioned linear representation in terms of Leaf Area Index. The consistency of the estimation methods derived from the allometric model was tested using data from a Z. marina meadow. Consequently, the improved method is expected to become a valuable tool for the reduction of the uncertainty associated with the estimation of above-ground biomass through the use of Leaf Area Index.

  15. Estimation of Tropical Forest Leaf Area Index Using Medium-Footprint Lidar

    NASA Astrophysics Data System (ADS)

    Sheldon, S. L.; Dubayah, R. O.; Clark, D. B.; Hofton, M. A.; Blair, J. B.

    2008-12-01

    As an important descriptor of forest canopy structure and productivity, leaf surface area strongly relates to respiration, photosynthesis, canopy dynamics, and other biophysical processes. Leaf Area Index (LAI), the amount of one sided leaf area per unit of ground area, has been an important parameter in a variety of ecosystem models. We explore the use of medium-footprint airborne scanning lidar to estimate the spatial distribution of LAI at a landscape scale. Direct estimates of LAI were collected on vertical transects at 71 sites stratified across a tropical wet forest landscape at La Selva Biological Station in Costa Rica. Vertical canopy structure information was collected by the Laser Vegetation Imaging Sensor (LVIS) over La Selva in March of 2005. We analyze the relationship between field-derived LAI estimates and three-dimensional lidar-derived canopy structure information, specifically waveforms and waveform-derived metrics. We also assess the potential of lidar data to scale local estimates of LAI to the landscape level.

  16. Estimation of water flux in urban area using eddy covariance measurements in Riverside, Southern California

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Micrometeorological methods can direct measure the sensible and latent heat flux in specific sites and provide robust estimates of the evaporative fraction (EF), which is the fraction of available surface energy contained in latent heat. Across a vegetation coverage gradient in urban area, an empir...

  17. A small area analysis estimating the prevalence of addiction to opioids in Barcelona, 1993

    PubMed Central

    Brugal, M. T.; Domingo-Salvany, A.; Maguire, A.; Cayla, J. A.; Villalbi, J. R.; Hartnoll, R.

    1999-01-01

    STUDY OBJECTIVE: To determine the distribution of opioid use prevalence in small areas and its relation with socioeconomic indicators. DESIGN: Capture-recapture was applied using data from the Barcelona Drug Information System for 1993 (treatment demands, hospital emergency room visits, deaths from heroin acute adverse reaction and pre-trial prison admissions). To avoid dependence between sources, a log-linear regression model with interactions was fitted. For small neighbourhoods, where capture-recapture estimates were not obtainable, the Heroin Problem Index (HPI) was used to predict prevalence rates from a regression model. The correlation between estimated opioid use prevalence by neighbourhoods and their socioeconomic level was computed. MAIN RESULTS: The city's estimated prevalence was 12.9 opioid addicts per 1000 inhabitants aged 15 to 44 years (95% CI: 10.1, 17.2), which represents 9176 persons. The highest rate was found in the inner city neighbourhood. Comparing rates obtained for each neighbourhood with their unemployment rates, a high correlation coefficient was obtained (r = 0.80, p < 0.001). CONCLUSION: The main contribution of this study is that of combining capture-recapture with the HPI to produce small area prevalence estimates, which would not have been possible using only one method. Areas with higher socioeconomic status showed proportionally low addiction prevalences, but in depressed areas, prevalences varied widely.   PMID:10562867

  18. A study of area clustering using factor analysis in small area estimation (An analysis of per capita expenditures of subdistricts level in regency and municipality of Bogor)

    NASA Astrophysics Data System (ADS)

    Wahyudi, Notodiputro, Khairil Anwar; Kurnia, Anang; Anisa, Rahma

    2016-02-01

    Empirical Best Linear Unbiased Prediction (EBLUP) is one of indirect estimating methods which used to estimate parameters of small areas. EBLUP methods works in using auxiliary variables of area while adding the area random effects. In estimating non-sampled area, the standard EBLUP can no longer be used due to no information of area random effects. To obtain more proper estimation methods for non sampled area, the standard EBLUP model has to be modified by adding cluster information. The aim of this research was to study clustering methods using factor analysis by means of simulation, provide better cluster information. The criteria used to evaluate the goodness of fit of the methods in the simulation study were the mean percentage of clustering accuracy. The results of the simulation study showed the use of factor analysis in clustering has increased the average percentage of accuracy particularly when using Ward method. The method was taken into account to estimate the per capita expenditures based on Small Area Estimation (SAE) techniques. The method was eventually used to estimate the per capita expenditures from SUSENAS and the quality of the estimates was measured by RMSE. This research has shown that the standard-modified EBLUP model provided with factor analysis better estimates when compared with standard EBLUP model and the standard-modified EBLUP without the factor analysis. Moreover, it was also shown that the clustering information is important in estimating non sampled area.

  19. Age Estimation of African Lions Panthera leo by Ratio of Tooth Areas.

    PubMed

    White, Paula A; Ikanda, Dennis; Ferrante, Luigi; Chardonnet, Philippe; Mesochina, Pascal; Cameriere, Roberto

    2016-01-01

    Improved age estimation of African lions Panthera leo is needed to address a number of pressing conservation issues. Here we present a formula for estimating lion age to within six months of known age based on measuring the extent of pulp closure from X-rays, or Ratio Of tooth AReas (ROAR). Derived from measurements taken from lions aged 3-13 years for which exact ages were known, the formula explains 92% of the total variance. The method of calculating the pulp/tooth area ratio, which has been used extensively in forensic science, is novel in the study of lion aging. As a quantifiable measure, ROAR offers improved lion age estimates for population modeling and investigations of age-related mortality, and may assist national and international wildlife authorities in judging compliance with regulatory measures involving age.

  20. Age Estimation of African Lions Panthera leo by Ratio of Tooth Areas.

    PubMed

    White, Paula A; Ikanda, Dennis; Ferrante, Luigi; Chardonnet, Philippe; Mesochina, Pascal; Cameriere, Roberto

    2016-01-01

    Improved age estimation of African lions Panthera leo is needed to address a number of pressing conservation issues. Here we present a formula for estimating lion age to within six months of known age based on measuring the extent of pulp closure from X-rays, or Ratio Of tooth AReas (ROAR). Derived from measurements taken from lions aged 3-13 years for which exact ages were known, the formula explains 92% of the total variance. The method of calculating the pulp/tooth area ratio, which has been used extensively in forensic science, is novel in the study of lion aging. As a quantifiable measure, ROAR offers improved lion age estimates for population modeling and investigations of age-related mortality, and may assist national and international wildlife authorities in judging compliance with regulatory measures involving age. PMID:27089506

  1. Age Estimation of African Lions Panthera leo by Ratio of Tooth Areas

    PubMed Central

    Ikanda, Dennis; Ferrante, Luigi; Chardonnet, Philippe; Mesochina, Pascal; Cameriere, Roberto

    2016-01-01

    Improved age estimation of African lions Panthera leo is needed to address a number of pressing conservation issues. Here we present a formula for estimating lion age to within six months of known age based on measuring the extent of pulp closure from X-rays, or Ratio Of tooth AReas (ROAR). Derived from measurements taken from lions aged 3–13 years for which exact ages were known, the formula explains 92% of the total variance. The method of calculating the pulp/tooth area ratio, which has been used extensively in forensic science, is novel in the study of lion aging. As a quantifiable measure, ROAR offers improved lion age estimates for population modeling and investigations of age-related mortality, and may assist national and international wildlife authorities in judging compliance with regulatory measures involving age. PMID:27089506

  2. Area estimation of environmental phenomena from NOAA-n satellite data. [TIROS N satellite

    NASA Technical Reports Server (NTRS)

    Tappan, G. (Principal Investigator); Miller, G. E.

    1982-01-01

    A technique for documenting changes in size of NOAA-n pixels in order to calibrate the data for use in performing area calculations is described. Based on Earth-satellite geometry, a function for calculating the effective pixel size, measured in terms of ground area, on any given pixel was derived. The equation is an application of the law of sines plus an arclength formula. Effective pixel dimensions for NOAA 6 and 7 satellites for all pixels between nadir and the extreme view angles are presented. The NOAA 6 data were used to estimate the areas of several lakes, with an accuracy within 5%. Sources of error are discussed.

  3. Maximal area and conformal welding heuristics for optimal slice selection in splenic volume estimation

    NASA Astrophysics Data System (ADS)

    Gutenko, Ievgeniia; Peng, Hao; Gu, Xianfeng; Barish, Mathew; Kaufman, Arie

    2016-03-01

    Accurate estimation of splenic volume is crucial for the determination of disease progression and response to treatment for diseases that result in enlargement of the spleen. However, there is no consensus with respect to the use of single or multiple one-dimensional, or volumetric measurement. Existing methods for human reviewers focus on measurement of cross diameters on a representative axial slice and craniocaudal length of the organ. We propose two heuristics for the selection of the optimal axial plane for splenic volume estimation: the maximal area axial measurement heuristic and the novel conformal welding shape-based heuristic. We evaluate these heuristics on time-variant data derived from both healthy and sick subjects and contrast them to established heuristics. Under certain conditions our heuristics are superior to standard practice volumetric estimation methods. We conclude by providing guidance on selecting the optimal heuristic for splenic volume estimation.

  4. Historical Tank Content Estimate for the Northwest Quandrant of the Hanford 200 East Area

    SciTech Connect

    Brevick, C.H.; Gaddis, L.A.; Pickett, W.W.

    1994-06-01

    Historical Tank Content Estimate of the Northeast Quadrant provides historical evaluations on a tank by tank basis of the radioactive mixed wastes stored in the underground single-shell tanks of the Hanford 200 East area. This report summaries historical information such at waste history, temperature, tank integrity, inventory estimates and tank level history on a tank by tank basis. Tank Farm aerial photos and in-tank photos of each tank are provided. A brief description of instrumentation methods used for waste tank surveillance, along with the components of the data management effort, such as waste status and Transaction Record Summary, Tank Layering Model, Defined Waste Types, and Inventory Estimates to generate these tank content estimates are also given in this report.

  5. Soil volume estimation in debris flow areas using lidar data in the 2014 Hiroshima, Japan rainstorm

    NASA Astrophysics Data System (ADS)

    Miura, H.

    2015-10-01

    Debris flows triggered by the rainstorm in Hiroshima, Japan on August 20th, 2014 produced extensive damage to the built-up areas in the northern part of Hiroshima city. In order to consider various emergency response activities and early-stage recovery planning, it is important to evaluate the distribution of the soil volumes in the debris flow areas immediately after the disaster. In this study, automated nonlinear mapping technique is applied to light detection and ranging (LiDAR)-derived digital elevation models (DEMs) observed before and after the disaster to quickly and accurately correct geometric locational errors of the data. The soil volumes generated from the debris flows are estimated by subtracting the pre- and post-event DEMs. The geomorphologic characteristics in the debris flow areas are discussed from the distribution of the estimated soil volumes.

  6. Fluorescence of crop residue: postmortem analysis of crop conditions

    NASA Astrophysics Data System (ADS)

    McMurtrey, James E., III; Kim, Moon S.; Daughtry, Craig S. T.; Corp, Lawrence A.; Chappelle, Emmett W.

    1997-07-01

    Fluorescence of crop residues at the end of the growing season may provide an indicator of the past crop's vegetative condition. Different levels of nitrogen (N) fertilization were applied to field grown corn and wheat at Beltsville, Maryland. The N fertilizer treatments produce a range of physiological conditions, pigment concentrations, biomass levels, and grain yields that resulted in varying growth and stress conditions in the living crops. After normal harvesting procedures the crop residues remained. The fluorescence spectral characteristics of the plant residues from crops grown under different levels of N nutrition were analyzed. The blue-green fluorescence response of in-vitro residue biomass of the N treated field corn had different magnitudes. A blue-green- yellow algorithm, (460/525)*600 nm, gave the best separations between prior corn growth conditions at different N fertilization levels. Relationships between total dry biomass, the grain yield, and fluorescence properties in the 400 - 670 nm region of the spectrum were found in both corn and wheat residues. The wheat residue was analyzed to evaluate the constituents responsible for fluorescence. A ratio of the blue-green, 450/550 nm, images gave the best separation among wheat residues at different N fertilization levels. Fluorescence of extracts from wheat residues showed inverse fluorescence intensities as a function of N treatments compared to that of the intact wheat residue or ground residue samples. The extracts also had an additional fluorescence emission peak in the red, 670 nm. Single band fluorescence intensity in corn and wheat residues is due mostly to the quantity of the material on the soil surface. Ratios of fluorescence bands varied as a result of the growth conditions created by the N treatments and are thought to be indicative of the varying concentrations of the plant residues fluorescing constituents. Estimates of the amount and cost effectiveness of N fertilizers to satisfy

  7. Model estimation of the role of urban areas in global CO{sub 2} dynamics

    SciTech Connect

    Krapivin, V.F.; Vilkova, L.P.; Rochon, G.L.; Hicks, D.R.

    1996-12-31

    The proposed Global Carbon Cycle Model (GCCM) considers the atmosphere, oceans and land masses as its main reservoirs. The oceans are subdivided into two reservoirs: a surface layer and deep-water mass sector. Land areas in the GCCM are divided into areas covering four degrees of latitude and five degrees of longitude. Each vegetated area belongs to one of thirty ecosystems, according to the Bazilevich classification, with additional urban and agricultural ecosystems, or is considered unvegetated. Urban areas are considered as part of the earth surface cell and distribution of the carbon excess dynamics of these cells is given in the GCCM input. Within the framework of scenarios of urban area functions, the carbon dioxide kinetics in the atmosphere are estimated.

  8. Estimating species - area relationships by modeling abundance and frequency subject to incomplete sampling.

    PubMed

    Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-07-01

    Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a

  9. Estimating species - area relationships by modeling abundance and frequency subject to incomplete sampling.

    PubMed

    Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-07-01

    Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a

  10. Estimating extinction from species--area relationships: why the numbers do not add up.

    PubMed

    He, Fangliang; Hubbell, Stephen

    2013-09-01

    Researchers commonly use species-area relationships (SAR) to estimate extinction rates caused by habitat loss by reversing the SAR, extrapolating backward from area to calculate expected species loss. We have previously shown that the backward SAR method considerably overestimates extinction rates due to a previously unrecognized sampling artifact. Jacob Bock Axelsen, Uri Roll, Lewi Stone, and Andrew Solow recently argued that the backward SAR method is correct and the method does not overestimate extinction rates. In this paper, we further elaborate and clarify our previous results. We show that the backward SAR method gives the correct extinction rate only under a strict complementary-area sampling design, which is not used in practice because it requires knowing which species are endemic to the area of destroyed habitat, or the number of species in the complementary area. Because of this problem, researchers substitute a power-law model for the SAR in the backward SAR equation. However, this substitution violates the backward SAR method's requirement for complementary sampling. With this model substitution, the backward SAR equation is no longer correct, except in the special case of randomly distributed species. For the complementary sampling or random distribution of species, the first individual of a species to be encountered and the last individual to be encountered to lose the species are exchangeable (or the same individual). But this is not the case for other sampling designs or if species are not randomly distributed and explains why the backward SAR method fails to correctly estimate extinction rates. Our proofs and results are general and explain the widely recognized overestimation of extinction by the backward SAR method. We suggest future directions for developing general theory for estimating species extinction from species-area relationships. Until then, however, the backward SAR method should not be used to estimate species extinction in practice.

  11. Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

    USGS Publications Warehouse

    Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

    2016-01-01

    Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied

  12. Use of UAS Remote Sensing Data (AggieAir) to Estimate Crop ET at High Spatial Resolution

    NASA Astrophysics Data System (ADS)

    ELarab, M.; Torres, A.; Nieto Solana, H.; Kustas, W. P.; Song, L.; Alfieri, J. G.; Prueger, J. H.; McKee, L.; Anderson, M. C.; Jensen, A.; McKee, M.; Alsina, M. M.

    2015-12-01

    Estimation of the spatial distribution of evapotranspiration (ET) based on remotely sensed imagery has become useful for managing water in irrigated agricultural at various spatial scales. Currently, data acquired by conventional satellites (Landsat, ASTER, etc.) lack the needed spatial resolution to capture variability of interest to support evapotranspiration estimates. In this study, an unmanned aerial system (UAS), called AggieAirTM, was used to acquire high-resolution imagery in the visual, near infrared (0.15m resolution) and thermal infrared spectra (0.6m resolution). AggieAir flew over two study sites in Utah and Central Valley of California. The imagery was used as input to a surface energy balance model based on the Mapping Evapotranspiration with Internalized Calibration (METRIC) modeling approach. The discussion will highlight the ET estimation methodologies and the implications of having high resolution ET maps.

  13. Hydrogeology and ground-water quality in the Black Belt area of west-central Alabama, and estimated water use for aquaculture, 1990

    USGS Publications Warehouse

    Kidd, R.E.; Lambeth, D.S.

    1995-01-01

    Commercial production of catfish in west-central Alabama began about 1970, and by 1991 catfish ponds covered about 16,000 acres in the Black Belt area of the State. The rapid increase in catfish farming or aquaculture and the associated demand for ground water led the U.S. Geological Survey in cooperation with other Federal and State agencies in 1990 to initiate a study to better define the ground-water resources in the Black Belt area. The major aquifers in the study area are sand and gravel beds in the Eutaw, Gordo, and Coker Formations. Recharge to these aquifers occurs primarily in areas where those formations crop out. The average recharge to the major aquifers in the study area, as estimated from baseflow analysis of streams in the outcrop area, is 11.4 inches per year. Water from the major aquifers in the study area generally is of good quality and suitable for most uses. Water from the Eutaw aquifer, however, contains chloride in concentrations greater than 500 milligrams per liter in central Greene County and in downdip areas in Marengo and Wilcox Counties and is not suitable for public water supply. Some ground water with elevated chloride concentrations is used for catfish farming in these areas, however. The total estimated water use for aquaculture in the study area in 1990 was 21.83