Meteorological satellite data: A tool to describe the health of the world's agriculture

Local area coverage data acquired aboard the TIROS-N satellite family by the advanced very high resolution radiometer systems was examined to determine the agricultural information current. Albedo differences between channel 2 and channel 1 of the advanced very high resolution radiometer LAC (called EVI) are shown to be closely correlated to the Ashburn vegetative index produced from LANDSAT multispectral scanner data which have been shown to vary in response to "greenness", soil moisture, and crop production. The statistical correlation between the EVI and the Ashburn Vegetative Index (+ or - 1 deg) is 0.86

Research correlation vegetation index of corn with speed of movement sensor and elevation of field

This paper presents field scouting of corn in order to determine the content of nitrogen in the green parts of the plants. The aim was to measure the vegetative index using two optical sensors by OptRx AGL Technology. The sensors are positioned at a distance of 3.5 m, individually observing five rows of corn. The speed of movement of the tractor and also elevation of field are varied. The measured vegetative index of the plants is correlated, in first, with the speed of the sensor on the platform. The measured vegetative index of the plants is correlated after that with elevation also. Both of that case are shown that the Normalised Difference Red Edge (NDRE) as represent of vegetative index is not correlated with speed and elevation. This Results represented with Pearson Correlation Coefficient and Spearman's Correlation Coefficient are statistical signatifical. This conclusions are valid only for short rang of speed and elevation research. Average speed was 6,39 km/hr and rang of elevation was 1.6 m (106.8-108.4 m)

Effects of decreasing resolution on spectral and spatial information content in an agricultural area

The effects of decreasing spatial resolution from 6 1/4 miles square to 50 miles square are described. The effects of increases in cell size is studied on; the mean and variance of spectral data; spatial trends; and vegetative index numbers. Information content changes on cadastral, vegetal, soil, water and physiographic information are summarized

Atmospheric effects on METSAT data

When using the J. V. Dave dataset, two channels of simulated METSAT advanced very high resolution radiometer (AVHRR) data compare favorably with actual data. Simulated NOAA6 and NOAA7 AVHRR data are presented as radiance profiles of reflected solar energy through atmosphere with three different aerosol levels. Effects of the atmosphere on the data are presented as functions of satellite view angle or pixel position on scanline. Vegetative index simultations are also profiled

Limited Area Coverage/High Resolution Picture Transmission (LAC/HRPT) data vegetative index calculation processor user's manual

The program, LACVIN, calculates vegetative indexes numbers on limited area coverage/high resolution picture transmission data for selected IJ grid sections. The IJ grid sections were previously extracted from the full resolution data tapes and stored on disk files

The environmental vegetation index: A tool potentially useful for arid land management

The NOAA-6 AVHRR data sets acquired over South Texas and Mexico during the spring of 1980 and after Hurricane Allen passed inland are analyzed. These data were processed to produce the Gray-McCrary Index (GMI's) for each pixel location over the selected area, which area contained rangeland and cropland, both irrigated and nonirrigated. The variations in the GMI's appear to reflect well the availability of water for vegetation. The GMI area maps are shown to delineate and to aid in defining the duration of drought; suggesting the possibility that time changes over a selected area could be useful for irrigation management

Using Canopies indices to Quantify the Economic optimum nitrogen rate in Spring Wheat

In-season N applications to spring wheat (Triticum aestivum L.) may increase profits and improve N fertilizer accuracy. The objectives were to develop a calibration tool employing normalized difference vegetative index (NDVI) and SPAD 502 chlorophyll meter (SPAD) measurements for calculating the differential from the economic optimum N rate (dEONR) at growth stages Z22, Z24, and Z31 to Z39 and provide N rate algorithms for use in applying N fertilizer at a variable rate. Sensing was conducted trials over 3 yr encompassing 10 site-years across Southeastern Buenos Aires Province, Argentina. The relationship between sensor indices and dEONR was evaluated by fitting quadratic plateau (QP) regression models. Statistically significant QP models were determined at the Z24, Z31, and Z39 growth stages. Relative SPAD (rSPAD) and relative NDVI (rNDVI) reduced variation and improved the calibration of measured N stress with the dEONR. For Z31 and Z39, the rSPAD had the best goodness of fit statistics when compared to rNDVI [adjusted R2 (adjR2)= 0.67 and 0.57 at Z31 and 0.68 and 0.52 at Z39, respectively]. However, adjustment at Z24 was higher for rNDVI (adjR2 = 0.53 and 0.61 for rSPAD and rNDVI, respectively). A single QP model to estimate the dEONR with 58% confidence was adjusted for the Z31 and Z39 growth stages. This indicates that the same calibration for N rate determination based on rSPAD or rNDVI values can be used during stem elongation in spring wheat. This model can be used as an N rate algorithm for applying N fertilizer in-season.Fil: Reussi Calvo, Nahuel Ignacio. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sainz Rozas, Hernan Rene. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Echeverria, Hernan Eduardo. Instituto Nacional de Tecnología Agropecuaria; Argentina. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; ArgentinaFil: Diovisalvi, Nadia Rosalia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Study to assess the importance of errors introduced by applying NOAA 6 and NOAA 7 AVHRR data as an estimator of vegetative vigor: Feasibility study of data normalization

The use of NOAA AVHRR data to map and monitor vegetation types and conditions in near real-time can be enhanced by using a portion of each GAC image that is larger than the central 25% now considered. Enlargement of the cloud free image data set can permit development of a series of algorithms for correcting imagery for ground reflectance and for atmospheric scattering anisotropy within certain accuracy limits. Empirical correction algorithms used to normalize digital radiance or VIN data must contain factors for growth stage and for instrument spectral response. While it is not possible to correct for random fluctuations in target radiance, it is possible to estimate the necessary radiance difference between targets in order to provide target discrimination and quantification within predetermined limits of accuracy. A major difficulty lies in the lack of documentation of preprocessing algorithms used on AVHRR digital data

REMOTE-SENSING METHODS OF INDICATOR ESTIMATIONS OF GARDENING TERRITORIES PLACED BY MINING INDUSTRY WASTE

Today across the world there are huge areas that are occupied by badlands left after intensive mining. Breeding dumps, sludge dumps, places of storage of ash and slag often represent a biological desert, which is difficult to remediate. For example, such places are sulfur rock dumps of mines in Donbas as a result of insufficient mineral nutrition and high acidity with sulfur concentration. Such zones show a low rate of self-growth and gardening. Mining wastes that accumulated for many years contain toxic components that are priority sources of environmental pollution

Computer program documentation for the patch subsampling processor

The programs presented are intended to provide a way to extract a sample from a full-frame scene and summarize it in a useful way. The sample in each case was chosen to fill a 512-by-512 pixel (sample-by-line) image since this is the largest image that can be displayed on the Integrated Multivariant Data Analysis and Classification System. This sample size provides one megabyte of data for manipulation and storage and contains about 3% of the full-frame data. A patch image processor computes means for 256 32-by-32 pixel squares which constitute the 512-by-512 pixel image. Thus, 256 measurements are available for 8 vegetation indexes over a 100-mile square