Impacts of NASA's remote sensing data on policy and decision making at state and local agencies in the United States

Kalluri, Satya; Gilruth, P.; Bergman, Ramona; Plante, R.

doi:10.1109/igarss.2002.1026223

Cited by 4 publications

(3 citation statements)

References 4 publications

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“…Site-specific management of crops and variable rate technologies rely heavily on affordable techniques to spatially monitor physiological status of crops and respond to tactical interventions, such as in-season nitrogen application [6]. Lack of fine spatial resolution and near real-time data compounded by high costs has hindered operational remote sensing applications at the field scale in the past [7]. This paper presents some results of on-going research in the application of the imagery available from an unmanned aerial vehicle (UAV) platform called AggieAir TM in the high spatial and temporal resolution remote sensing of plant nutrient status for a large field served by center pivot sprinkler systems.…”

Section: Introductionmentioning

confidence: 99%

Use of high-resolution multispectral imagery from an unmanned aerial vehicle in precision agriculture

Al-Arab

Torres‐Rua

Ticlavilca

et al. 2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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Precision agriculture requires high spatial management of the inputs to agricultural production. This requires that actionable information about crop and field status be acquired at the same high spatial resolution and at a temporal frequency appropriate for timely responses. This paper presents some results from an on-going project to explore the use of imagery collected from the use of a small unmanned aerial vehicle, called AggieAir, to estimate plant nitrogen and chlorophyll at approximately 13-cm resolution for a field of oats served by a center pivot sprinkler system. When combined with appropriate analytic tools, the AggieAir imagery can be successfully used to estimate plant nitrogen and chlorophyll levels at much finer than 1-m resolution.

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Section: Introductionmentioning

confidence: 99%

Use of high-resolution multispectral imagery from an unmanned aerial vehicle in precision agriculture

Al-Arab

Torres‐Rua

Ticlavilca

et al. 2013

2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS

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“…Irrigation scheduling aimed to replenish crop water requirements as quantified in evapotranspiration amounts under certain climatic conditions (Hunsakar and Pinter, 2003). Evapotranspiration is a term describing the transport of water into the atmosphere from surfaces, including evaporation from land surfaces and transpiration of vegetation (Allen et al, 1998;Hongjie et al, 2002;Kalluri et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Monthly Reference Evapotranspiration Modeling Using Gene Expression Programming From Minimum Climatic Data

Mattar

2015

Journal of Soil Sciences and Agricultural Engineering

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Evapotranspiration is a key factor for water balance, irrigation scheduling, and crop yield. Even though, Penman-Monteith FAO-56 (PMF-56) equation had estimated the highest accuracy reference evapotranspiration (ETo), it required complete climatic records, which may not be easily available. The present study is to develop and evaluate a gene expression programming (GEP) model for estimating mean monthly ETo using minimal number of climatic data. Climatic variables used to estimate ETo are maximum and minimum air temperature (Tmax and Tmin), mean relative humidity (RH), solar radiation (Rs), and wind speed at 2-m height (u2). The data used in the analysis refer to 32 weather stations available at different locations in Egypt through the CLIMWAT database. The PMF-56 method was used as the reference standard for evaluating the developed GEP models based on statistical criteria such as: index of agreement (IA) and the root mean square error (RMSE). The results showed that the accuracy of the GEP model significantly improved when either RH or u2 was used as additional input variables. The GEP model with the inputs: Tmax, Tmin, RH, and u2 showed the highest IA (0.991 and 0.990) and the lowest RMSE (0.426 mm d-1 and 0.430 mm d-1) for training and testing sets, respectively. Comparing the results of GEP models with other empirical models showed that ETo values estimated by using the GEP models are more accurate. Accordingly, the GEP technique can be employed successfully in modeling ETo from the available climatic data and allowed for providing simple algebraic formulas.

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“…The potential evaporation is the maximum value of the actual evaporation. Transpiration includes the vaporization of liquid water contained in plant tissues and vapor transfer to the atmosphere [2][3][4] .…”

Section: Introductionmentioning

confidence: 99%

Untitled

Kosa¹,

Pongput²

2007

ScienceAsia

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In the hydrological cycle and in water use, evapotranspiration is one of the most important components because it represents a loss of usable water from the hydrological supply. The purposes of this research are to examine the temporal trend of reference evapotranspiration and pan evaporation for the upper region, the lower region, and the whole catchment of the Chao Phraya River Basin, and to consider the spatial and temporal distribution of monthly reference evapotranspiration. To achieve these purposes, daily reference evapotranspiration from 1971 to 2002 was computed for each weather station using the FAO Penman-Monteith method. The average of monthly reference evapotranspiration in each weather station was calculated. Thereafter, this monthly reference evapotranspiration reference point for evapotranspiration was interpolated using the Co-Kriging interpolation to obtain a spatial value. From the results of this research it can be concluded that the trends of both reference evapotranspiration and pan evaporation in all the regions have decreased from 1971 to 2002 and that the spatial and temporal distribution of mean monthly reference evapotranspiration are affected by the changes in the meteorological variables for each month and for each different region.

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Impacts of NASA's remote sensing data on policy and decision making at state and local agencies in the United States

Cited by 4 publications

References 4 publications

Use of high-resolution multispectral imagery from an unmanned aerial vehicle in precision agriculture

Use of high-resolution multispectral imagery from an unmanned aerial vehicle in precision agriculture

Monthly Reference Evapotranspiration Modeling Using Gene Expression Programming From Minimum Climatic Data

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