排序方式： 共有16条查询结果，搜索用时 15 毫秒
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A Case Study on Forewarning of Yellow Rust Affected Areas on Wheat Crop Using Satellite Data 总被引：2，自引：0，他引：2
Sujay Dutta Suresh Kumar Singh Mukesh Khullar 《Journal of the Indian Society of Remote Sensing》2014,42(2):335-342
Objective of this study was to identify stripe rust affected areas of wheat crop as well as evaluation of remote sensing (RS) derived indices. Moderately low temperature and high humidity favour the growth of yellow rust. Most affected areas of Punjab are the foothill districts such as Gurdaspur, Hoshiarpur and Ropar. Occurrence of yellow rust is possible when maximum temperature for day is below 15 °C and Temperature difference of day’s maximum and minimum temperature is less than 5 °C during the early growth of wheat. Forecast of the infestation was done using 3 days forecast of weather data obtained from Weather Research and Forecasting (WRF) model at 5 km resolution. Weather forecast used was obtained from Meteorological and Oceanographic Satellite Data Archival System (MOSDAC) site and post infestation, identification of specific locations were done using multi-date IRS AWiFS data. It is an attempt for early detection through 3 days advance forewarning of weather which will be handy tool for planners to expedite relief measures in case of epidemic with a more focused zones of infestation as well as for crop insurers to know the location and extent of damage affected areas. 相似文献
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Jonathan Gewirtzman Sujay Natson Julie-Anne Richards Victoria Hoffmeister Alexis Durand Romain Weikmans 《Climate Policy》2018,18(8):1076-1086
After decades of pressure from vulnerable developing countries, the Warsaw International Mechanism on Loss and Damage (the WIM) was established at the nineteenth Conference of the Parties (COP 19) in 2013 to address costly damages from climate change. However, little progress has been made towards establishing a mechanism to fund loss and damage. The WIM's Executive Committee issued its first two-year workplan the following year at COP 20 which offered, among other things, a range of approaches to financing loss and damage programmes, which we review here. We provide brief overviews of each mechanism proposed by the WIM ExCom, describe their current applications, their statuses under the United Nations Framework Convention on Climate Change (UNFCCC), some of their advantages and disadvantages, and their current or potential application to loss and damage. We find that several of these mechanisms may be useful in supporting loss and damage programmes, but identify some key gaps. First, most of the mechanisms identified by the WIM ExCom are insurance schemes subsidized with voluntary contributions, which may not be adequate or reliable over time. Second, none were devised to apply to slow-onset events, or to non-economic losses and damages. That is, if harms are inflicted on parts of a society or its ecosystems that have no price, or if they occur gradually, they would probably not be covered by these mechanisms. Finally, the lack of a dedicated and adequate flow of finance to address the real loss and damage being experienced by vulnerable nations will require the use of innovative financial tools beyond those mentioned in the WIM ExCom workplan.
Key policy insights
Despite a full article of the 2015 Paris Agreement devoted to loss and damage, there is little international agreement on the scope of loss and damage programmes, and especially how they would be funded and by whom.
Most of the loss and damage funding mechanisms identified by the WIM ExCom are insurance schemes subsidized with voluntary contributions, which may burden the most vulnerable countries and may not be reliable over time.
None of the mechanisms were devised to apply to slow-onset events, or to non-economic losses and damages.
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Remote sensing of horticultural plantations in Kumarsain tehsil in Shimla district, Himachal Pradesh
M M Kimothi M H Kalubarme Sujay Dutta Rajendra Thapa R K Sood 《Journal of the Indian Society of Remote Sensing》1997,25(1):19-26
The favourable agroclimatic conditions for orchards especially apples have increased the acreages in Himachal Pradesh (HP) which has significantly contributed in the growth of state economy. Realizing the importance of horticulture in HP and its changing scenario of the land use/land cover, a study was conducted to identify and map apple and almond plantations in the Kumarsain tehsil of Shimla district using Remote Sensing (RS) techniques. IRS-IB LISS-II False Colour Composite (FCC) diapositives of October 27, March 30 and April 20, 1992 were visually analysed for mapping apple and almond plantations. The results indicate that IRS LISS-II data of April 20 on 1∶50,000 scale was found very useful for identification and mapping of apple and almond plantations in this region. Accuracy of interpretation was also tested on sample basis assuming a binomial distribution for the probability of success/failure of sample points. The overall interpretation accuracy assessed based on 40 sample points was found to be 87 per cent at 90 per cent confidence limits. 相似文献
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Nitrogen uptake and denitrification in restored and unrestored streams in urban Maryland, USA 总被引：2，自引：0，他引：2
Carolyn A. Klocker Sujay S. Kaushal Peter M. Groffman Paul M. Mayer Raymond P. Morgan 《Aquatic Sciences - Research Across Boundaries》2009,71(4):411-424
There is growing interest in rates of nitrate uptake and denitrification in restored streams to better understand the effects
of restoration on nitrogen processing. This study quantified nitrate uptake in two restored and two unrestored streams in
Baltimore, Maryland, USA using nitrate additions, denitrification enzyme assays, and a 15N isotope tracer addition in one of the urban restored streams, Minebank Run. Restoration included either incorporation of
stormwater ponds below a storm drain and catch basins to attenuate flow or hydrologic “reconnection” of a stream channel to
its floodplain. Stream restoration was conducted for restoring aging sanitary and bridge infrastructure and introducing some
stormwater management in watersheds developed prior to current regulations. Denitrification potential in sediments was variable
across streams, whereas nitrate uptake length appeared to be significantly correlated to surface water velocity, which was
low in the restored streams during summer baseflow conditions. Uptake length of NO3
−–N in Minebank Run estimated by 15N tracer addition was 556 m. Whole stream denitrification rates in Minebank Run were 153 mg NO3
−–N m−2 day−1, and approximately 40% of the daily load of nitrate was estimated to be removed via denitrification over a distance of 220.5 m
in a stream reach designed to be hydrologically “connected” to its floodplain. Increased hydrologic residence time in Minebank
Run during baseflow likely influenced rates of whole stream denitrification, suggesting that hydrologic residence time may
be a key factor influencing N uptake and denitrification. Restoration approaches that increase hydrologic “connectivity” with
hyporheic sediments and increase hydrologic residence time may be useful for stimulating denitrification. More work is necessary,
however, to examine changes in denitrification rates in restored streams across different seasons, variable N loads, and in
response to the “flashy” hydrologic flow conditions during storms common in urban streams. 相似文献
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Sujay V. Kumar Rolf H. Reichle Christa D. Peters-Lidard Randal D. Koster Xiwu Zhan Wade T. Crow John B. Eylander Paul R. Houser 《Advances in water resources》2008
The Land Information System (LIS) is an established land surface modeling framework that integrates various community land surface models, ground measurements, satellite-based observations, high performance computing and data management tools. The use of advanced software engineering principles in LIS allows interoperability of individual system components and thus enables assessment and prediction of hydrologic conditions at various spatial and temporal scales. In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms. These capabilities are demonstrated here in a suite of experiments that use the ensemble Kalman filter (EnKF) and assimilation through direct insertion. In a soil moisture experiment, we discuss the impact of differences in modeling approaches on assimilation performance. Provided careful choice of model error parameters, we find that two entirely different hydrological modeling approaches offer comparable assimilation results. In a snow assimilation experiment, we investigate the relative merits of assimilating different types of observations (snow cover area and snow water equivalent). The experiments show that data assimilation enhancements in LIS are uniquely suited to compare the assimilation of various data types into different land surface models within a single framework. The high performance infrastructure provides adequate support for efficient data assimilation integrations of high computational granularity. 相似文献
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Relationship between C:N ratios of lake sediments, organic matter sources, and historical deforestation in Lake Pleasant, Massachusetts, USA 总被引：5，自引：0，他引：5
The C:N ratios of lake sediments may reflect proportions of terrestrial and algal carbon contributing to accumulation of sediment. This possibility was tested in Lake Pleasant, Massachussetts, USA which underwent watershed deforestation in about 1780 A.D. The C:N profile of a 70-cm sediment core clearly reflected deforestation through a rise in C:N ratio caused by an increase in watershed contributions to sedimentary carbon. Spatial variability of C:N in modern surficial sediments is small compared to the change caused by deforestation. 相似文献
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Sujay Dutta S.A. Sharma A.P. Khera Ajai M. Yadav R.S. Hooda K.E. Mothikumar M.L. Manchanda 《ISPRS Journal of Photogrammetry and Remote Sensing》1994,49(6)
The accuracy of cotton crop classification using satellite data has been assessed with respect to a detailed land cover map prepared by field survey. The effect of spatial resolution on classification accuracy was studied using LISS-I (spatial resolution 72.6 m) and LISS-II data (spatial resolution 36.25 m) of the Indian remote sensing satellite IRS-1B. The performances of the maximum likelihood and the minimum distance to mean as classifiers have also been assessed. LISS-II data have been found to give a higher classification accuracy. The estimate of cotton acreage using LISS-II data was closer to that obtained from the base map. The maximum likelihood classifier (MXL) and the minimum distance to mean (MDM) classifier performed equally well. 相似文献
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