scholarly journals Optical sensors for variable rate nitrogen application in dairy pastures

2017 ◽  
Vol 79 ◽  
pp. 223-227
Author(s):  
K. Wigley ◽  
J.L. Owens ◽  
J.A.K. Trethewey ◽  
D.C. Ekanayake ◽  
R.L. Roten ◽  
...  
Keyword(s):  
Optical Sensors ◽  
Vegetation Index ◽  
N Uptake ◽  
Variable Rate ◽  
Water Index ◽  
Foliar N ◽  
Normalised Difference Vegetation Index ◽  
Fertiliser Application ◽  
Vegetative Indices ◽  
Simple Ratio

Reducing the amount of nitrogen (N) fertiliser applied to dairy pastures down to agronomically optimised levels would have positive economic and environmental results. The ability of commercially available optical sensors to estimate biomass yield and foliar-N uptake in pastures was investigated. Vegetative indices (Simple Ratio, SR; Water Index, WI; and Normalised Difference Vegetation Index, NDVI) from two active optical reflectance sensors (N-Sensor, Yara; and Greenseeker, Trimble) were compared with manually measured biomass and N-uptake in above-ground foliage. There were three measurements over time, from pastures that had received different N fertiliser applications rates (0, 10, 20, 40 and 80 kg N/ha). It was found that the sensors were able to detect differences in biomass and foliar N-uptake following defoliation of grazed pastures. The tested optical sensors have the potential to inform a real-time variable rate fertiliser application system. Keywords: pasture, nitrogen, optical sensors

Advances in precision agriculture in south-eastern Australia. I. A regression methodology to simulate spatial variation in cereal yields using farmers' historical paddock yields and normalised difference vegetation index

2009 ◽  
Vol 60 (9) ◽  
pp. 844 ◽  
Author(s):  
P. D. Fisher ◽  
M. Abuzar ◽  
M. A. Rab ◽  
F. Best ◽  
S. Chandra
Keyword(s):  
Linear Relationship ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Yield Variability ◽  
Variable Rate ◽  
Management Options ◽  
Yield Data ◽  
Alternative Management ◽  
Financial Benefits ◽  
Normalised Difference Vegetation Index

Despite considerable interest by Australian farmers in precision agriculture (PA), its uptake has been low. Analysis of the possible financial benefits of alternative management options that are based on the underlying patterns of observed spatial and temporal yield variability in a paddock could increase farmer confidence in adopting PA. The cost and difficulty in collecting harvester yield maps have meant that spatial yield data are generally not available in Australia. This study proposes a simple, economical and easy to use approach to generate simulated yield maps by using paddock-specific relationships between satellite normalised difference vegetation index (NDVI) and the farmer’s average paddock yield records. The concept behind the approach is illustrated using a limited dataset. For each of 12 paddocks in a property where a farmer’s paddock-level yield data were available for 3–5 years, the paddock-level yields showed a close to linear relationship with paddock-level NDVI across seasons. This estimated linear relationship for each paddock was used to simulate mean yields for the paddock at the subpaddock level at which NDVI data were available. For one paddock of 167 ha, for which 4 years of harvester yield data and 6 years of NDVI data were available, the map of simulated mean yield was compared with the map of harvester mean yield. The difference between the two maps, expressed as percentage deviation from the observed mean yield, was <20% for 63% of the paddock and <40% for 78% of the paddock area. For 3 seasons when there were both harvester yield data and NDVI data, the individual season simulated yields were within 30% of the observed yields for over 70% of the paddock area in 2 of the seasons, which is comparable with spatial crop modelling results reported elsewhere. For the third season, simulated yields were within 30% of the observed yield in only 22% of the paddock, but poor seasonal conditions meant that 40% of the paddock yielded <100 kg/ha. To illustrate the type of financial analysis of alternative management options that could be undertaken using the simulated yield data, a simple economic analysis comparing uniform v. variable rate nitrogen fertiliser is reported. This indicated that the benefits of using variable rate technology varied considerably between paddocks, depending on the degree of spatial yield variability. The proposed simulated yield mapping requires greater validation with larger datasets and a wider range of sites, but potentially offers growers and land managers a rapid and cost-effective tool for the initial estimation of subpaddock yield variability. Such maps could provide growers with the information necessary to carry out on-farm testing of the potential benefits of using variable applications of agronomic inputs, and to evaluate the financial benefits of greater investment in PA technology.

scholarly journals Assessment of pine aboveground biomass within Northern Steppe of Ukraine using Sentinel-2 data

2020 ◽  
Vol 66 (No. 8) ◽  
pp. 339-348
Author(s):  
Viktoriia Lovynska ◽  
Yuriy Buchavyi ◽  
Petro Lakyda ◽  
Svitlana Sytnyk ◽  
Yuriy Gritzan ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Vegetation Index ◽  
Spectral Characteristics ◽  
Free Access ◽  
Biophysical Parameters ◽  
Normalised Difference Vegetation Index ◽  
Pine Stands ◽  
Predicted Values ◽  
Vegetative Indices ◽  
Sentinel 2

The present study offers the results of the spectral characteristics, calculated vegetative indices and biophysical parameters of pine stands of the Northern Steppe of Ukraine region obtained using Sentinel-2 data. For the development of regression models with the prediction of the biomass of pine forests using the obtained spectral characteristics, we used the results of the assessment of the aboveground biomass by the method of field surveys. The results revealed the highest correlation relations between the parameters of the general and trunk biomass with the normalised difference vegetation index (NDVI) and transformed vegetation index (TVI) vegetative indices and the fraction of absorbed photosynthetic active radiation (FARAP) and fraction of vegetation cover (FCOVER) biophysical parameters. To generate the models of determining the forest aboveground biomass (AGB), we used both the single- and two-factor models, the most optimum of which were those containing the NDVI predictor separately and in combination with the FCOVER predictor. The predicted values of the total AGB for the mentioned models equalled 32.5 to 236.3 and 39.9 to 253.4 t·ha<sup>–1</sup>. We performed mapping of the AGB of pine stands of the Northern Steppe using multi-spectral Sentinel-2 images, particularly the spectral characteristics of their derivatives (vegetative indices, biophysical parameters). This study demonstrated promising results for conducting an AGB-mapping of pine woods in the studied region using free-access resources.

Estimating pasture biomass with active optical sensors

2017 ◽  
Vol 8 (2) ◽  
pp. 754-757 ◽  
Author(s):  
K. Andersson ◽  
M. Trotter ◽  
A. Robson ◽  
D. Schneider ◽  
L. Frizell ◽  
...  
Keyword(s):  
Perennial Ryegrass ◽  
Optical Sensors ◽  
Tall Fescue ◽  
Festuca Arundinacea ◽  
Vegetation Index ◽  
Calibration Data ◽  
Optimal Model ◽  
Plate Height ◽  
Normalised Difference Vegetation Index ◽  
Dry Biomass

We investigated relationship between pasture biomass and measures of height and NDVI (normalised difference vegetation index). The pastures were tall fescue (Festuca arundinacea), perennial ryegrass (Lolium perenne), and phalaris (Phalaris aquatica) located in Tasmania, Victoria and in the Northern Tablelands of NSW, Australia. Using the Trimble® GreenSeeker® Handheld active optical sensor (AOS) to measure NDVI, and a rising plate meter, the optimal model to estimate green dry biomass (GDM) during two years was a combination of NDVI and falling plate height index. The combined index was significantly correlated with GDM in each region during winter and spring (r2=0.62–0.77, P<0.001). Regional calibrations provided a smaller error in estimates of green biomass, required for potential application in the field, compared to a single overall calibration. Data collected in a third year will be used to test the accuracy of the models.

scholarly journals Optical crop sensor for variable-rate nitrogen fertilization in corn: i - plant nutrition and dry matter production

2013 ◽  
Vol 37 (5) ◽  
pp. 1288-1298 ◽  
Author(s):  
Jardes Bragagnolo ◽  
Telmo Jorge Carneiro Amado ◽  
Rodrigo da Silveira Nicoloso ◽  
Joerg Jasper ◽  
Junior Kunz ◽  
...  
Keyword(s):  
Nitrogen Fertilization ◽  
Plant Nutrition ◽  
Dry Matter ◽  
Vegetation Index ◽  
N Uptake ◽  
Climatic Conditions ◽  
Dry Matter Production ◽  
Variable Rate ◽  
N Content ◽  
Matter Production

Variable-rate nitrogen fertilization (VRF) based on optical spectrometry sensors of crops is a technological innovation capable of improving the nutrient use efficiency (NUE) and mitigate environmental impacts. However, studies addressing fertilization based on crop sensors are still scarce in Brazilian agriculture. This study aims to evaluate the efficiency of an optical crop sensor to assess the nutritional status of corn and compare VRF with the standard strategy of traditional single-rate N fertilization (TSF) used by farmers. With this purpose, three experiments were conducted at different locations in Southern Brazil, in the growing seasons 2008/09 and 2010/11. The following crop properties were evaluated: above-ground dry matter production, nitrogen (N) content, N uptake, relative chlorophyll content (SPAD) reading, and a vegetation index measured by the optical sensor N-Sensor® ALS. The plants were evaluated in the stages V4, V6, V8, V10, V12 and at corn flowering. The experiments had a completely randomized design at three different sites that were analyzed separately. The vegetation index was directly related to above-ground dry matter production (R² = 0.91; p<0.0001), total N uptake (R² = 0.87; p<0.0001) and SPAD reading (R² = 0.63; p<0.0001) and inversely related to plant N content (R² = 0.53; p<0.0001). The efficiency of VRF for plant nutrition was influenced by the specific climatic conditions of each site. Therefore, the efficiency of the VRF strategy was similar to that of the standard farmer fertilizer strategy at sites 1 and 2. However, at site 3 where the climatic conditions were favorable for corn growth, the use of optical sensors to determine VRF resulted in a 12 % increase in N plant uptake in relation to the standard fertilization, indicating the potential of this technology to improve NUE.

scholarly journals Characterising Rice (Oryza indica) Ecology in East and Southern Eastern Plateau of Odisha using Multi Source Remote Sensing

2021 ◽  
pp. 37-47
Author(s):  
M. Satya Swarupa Rani ◽  
Anima Biswal ◽  
B. S. Rath
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Vegetation Index ◽  
Regional Scale ◽  
Vegetation Indices ◽  
Ecological Condition ◽  
Water Index ◽  
Normalised Difference Vegetation Index ◽  
Spectral Vegetation Indices ◽  
Block Level

Rice is the most important crop of Odisha occupying 41.24% of net sown area in Kharif season and contributing 65.85 % of total food grain production of Odisha state and this is being cultivated in various types environmental and ecological condition. Assessment of rice phenology is prime for management and yield prediction. In view of characterizing rice ecology in East and South Eastern Plateau from 2008 – 2018 to know the time series analysis , remote sensing tools were used . MODIS can0 acquire data over a wide area with high spatial and temporal resolutions easily providing regional scale information .In order to study the seasonal /annual as well as spatial variability of kharif rice vigour and wetness spectral vegetation indices like NDVI(Normalised Difference Vegetation Index),LSWI(Land surface water index) derived from 15 day composite 250 m data were analysed at block level for Odisha state. For studying the start of season variability, SASI index was used. The season maximum NDVI, LSWI were computed for the year 2008-2018 for kharif rice in East and Southern eastern coastal plain zone of Odisha and graphs were generated which shows the variability of the kharif rice vigour and wetness.

scholarly journals Ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca) on the basis of indices of remote sensing of land images

2016 ◽  
Vol 24 (1) ◽  
pp. 78-86
Author(s):  
O. M. Kunah ◽  
O. S. Papka
Keyword(s):  
Land Surface ◽  
Ecological Niche ◽  
Vegetation Index ◽  
Principal Component ◽  
Vegetative Cover ◽  
Asclepias Syriaca ◽  
Water Index ◽  
The Common ◽  
Common Milkweed Asclepias Syriaca ◽  
Vegetative Indices

The patterns of variation in vegetative indices received by means of data of remote land sensing are described as being dependant on geomorphological predictors and the sizes of agricultural fields in an experimental polygon within Poltava region. The possibilities of application of vegetative indices have been explored through ecogeographical determinants of the ecological niche of the common milkweed (Asclepias syriaca L.) and other weeds. On the basis of images of the land surface taken on 23 March and 27 August 2015 by the sensor control Operational Land Imager (OLI), installed on the satellite Landsat 8, vegetative indices have been calculated (AC-Index – aerosol/coastal index, Hydrothermal Composite, NDTI – Normalized Difference Tillage Index, NDVI – Normalized Difference Vegetation Index, VI – Vegetation Index, MNDW – Modified Normalized Difference Water Index, LSWI – Land Surface Water Index, NBR – Normalized Burn Ratio, M15). The data obtained have been subjected to principal component analysis and the revealed principal components have been interpreted with the help of regression analysis, in which geomorphological variables have been applied as predictors. It was possible to explain the trends of variability of the vegetative cover, formalized in the form of the principal component, by means of indices which quantitatively characterise features of relief. The various aspects of variation of vegetative cover have been shown to be characterised by the specificity of the influence of relief factors. A prominent aspect of the variation of the vegetative cover of agroecosystems is variability within a field. The degree of a variation of conditions is proportional to the size of a field. Large fields occupy level plain positions. In turn, within small fields sources of variation are changes in ecological conditions which arise owing to unevenness of relief, which increases in proximity to gullies and ravines. We have identified the aspects of the variation of vegetative cover which by their nature can be considered as contributers to the growth of weeds in agroceonoses. Satellite imaging by Landsat does not allow direct identification of concentrations of weeds, but it can reveal complex changes in the landscape cover, which act as markers of the processes connected with development of weed vegetation. The procedure of further decoding of satellite images for the purpose of identification of weeds requires greater attention in this field of research.

scholarly journals Assessment of Urban Expansion and Associated Spatial Transformation of Chandannagar City, West Bengal

2020 ◽  
Vol 7 (4) ◽  
pp. 109-121
Author(s):  
Giyasuddin Siddique ◽  
Subhendu Ghosh ◽  
Arindam Roy
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Temporal Dynamics ◽  
Urban Expansion ◽  
Annual Growth Rate ◽  
Spatial Transformation ◽  
Remotely Sensed Data ◽  
Water Index ◽  
Normalised Difference Vegetation Index ◽  
The City

The Chandannagar city, as a former French colony and a historic trading centre, has witnessed a steady growth throughout the French colonial era, and the process is still in action even today. Such urban extension has altered the land use/cover (LULC) fabric both in the core and fringe areas by transforming the natural landscape. The prime goals of the study are to assess the magnitude of urban expansion of the city from 1991 to 2016 and its consequent spatial transformation by using geospatial techniques. Three indices, that is, Built-up Index (BUI), Normalised Difference Vegetation Index (NDVI) and Modified Normalised Difference Water Index (MNDWI) are employed to perceive the spatio-temporal dynamics of LULC from the remotely sensed data. Annual Growth Rate (AGR) and Land Use Integrated Index (LDI) are used to evaluate the rate, magnitude, and nature of changes. The results reveal that the rapid increase in built-up area from 7.9 sq. Km. in 1991 to 14.45 sq. Km. in 2016 has transformed nearly 51.52% of the non-forest vegetation covers and 58.18% of the water bodies of the city during the observation period.

scholarly journals Predicting terrestrial dispersal corridors of the invasive African clawed frog Xenopus laevis in Portugal

NeoBiota ◽  
2021 ◽  
Vol 64 ◽  
pp. 103-118
Author(s):  
Philipp Ginal ◽  
Francisco D. Moreira ◽  
Raquel Marques ◽  
Rui Rebelo ◽  
Dennis Rödder
Keyword(s):  
Invasive Species ◽  
Xenopus Laevis ◽  
Vegetation Index ◽  
Stepping Stones ◽  
Dispersal Patterns ◽  
Water Index ◽  
African Clawed Frog ◽  
Normalised Difference Vegetation Index ◽  
Dispersal Corridors ◽  
Clawed Frog

Invasive species, such as the mainly aquatic African clawed frog Xenopus laevis, are a main threat to global biodiversity. The identification of dispersal corridors is necessary to restrict further expansion of these species and help to elaborate management plans for their control and eradication. Here we use remote sensing derived resistance surfaces, based on the normalised difference vegetation index (NDVI) and the normalised difference water index (NDWI) accounting for behavioural and physiological dispersal limitations of the species, in combination with elevation layers, to determine fine scale dispersal patterns of invasive populations of X. laevis in Portugal, where the frog had established populations in two rivers. We reconstruct past dispersal routes between these two invaded rivers and highlight high risk areas for future expansion. Our models suggest terrestrial dispersal corridors that connect both invaded rivers and identify artificial water bodies as stepping stones for overland movement of X. laevis. Additionally, we found several potential stepping stones into novel areas and provide concrete information for invasive species management.

Developing land-state maps of Tram Chim National Park in Vietnam based on monitoring results

2020 ◽  
Vol 963 (9) ◽  
pp. 53-64
Author(s):  
V.F. Kovyazin ◽  
Thi Lan Anh Dang ◽  
Viet Hung Dang
Keyword(s):  
National Park ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Likelihood Method ◽  
Wetland Area ◽  
Water Index ◽  
Effi Ciency ◽  
Normalized Difference Water Index ◽  
Specially Protected Natural Areas ◽  
Protected Natural Areas

Tram Chim National Park in Southern Vietnam is a wetland area included in the system of specially protected natural areas (SPNA). For the purposes of land monitoring, we studied Landsat-5 and Sentinel-2B images obtained in 1991, 2006 and 2019. The methods of normalized difference vegetation index (NDVI) and water objects – normalized difference water index (NDWI) were used to estimate the vegetation in National Park. The allocated land is classifi ed by the maximum likelihood method in ENVI 5.3 into categories. For each image, a statistical analysis of the land after classifi cation was performed. Between 1991 and 2019, land changes occurred in about 57 % of the Tram Chim National Park total area. As a result, the wetland area has signifi cantly reduced there due to climate change. However, the area of Melaleuca forests in Tram Chim National Park has increased due to the effi ciency of reforestation in protected areas. Melaleuca forests are also being restored.

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