Integrating satellite images and topographic data for mapping seasonal grazing management units in pastoral landscapes of eastern Africa

2022 ◽  
Vol 197 ◽  
pp. 104661
Author(s):  
Mohamed G. Shibia ◽  
Achim Röder ◽  
Francesco Pietro Fava ◽  
Marion Stellmes ◽  
Joachim Hill
Keyword(s):  
Satellite Images ◽  
Grazing Management ◽  
Eastern Africa ◽  
Management Units ◽  
Topographic Data ◽  
Pastoral Landscapes ◽  
Seasonal Grazing

Herbage mass thresholds rather than plant phenology are a more useful cue for grazing management decisions in the mid-north region of South Australia

2010 ◽  
Vol 32 (4) ◽  
pp. 379 ◽  
Author(s):  
Lewis P. Kahn ◽  
Judi M. Earl ◽  
Millie Nicholls
Keyword(s):  
Perennial Grass ◽  
South Australia ◽  
Plant Phenology ◽  
Perennial Grasses ◽  
Grazing Management ◽  
Plant Production ◽  
Sheep Grazing ◽  
Management Decisions ◽  
Basal Cover ◽  
Seasonal Grazing

Research was conducted in the mid-north of South Australia over the period 2000–05 to evaluate the effects of different grazing management cues on composition and production of a grassland. The management cues were based on calendar, plant phenology or herbage mass thresholds using grazing exclusion as a control. There were five grazing treatments: (i) regional practice (RP), where sheep grazed continuously for the period April–December; (ii) autumn rest, where sheep grazing was restricted to June–December; (iii) spring rest, where sheep grazing was restricted to April–August; (iv) high density and short duration (HDSD), where herbage mass thresholds determined when grazing occurred and for what duration; and (v) nil (NIL) grazing by domestic herbivores. Mean annual estimates of herbage mass were highest for NIL and HDSD and inclusion of the estimate of herbage consumption by sheep resulted in greatest primary plant production in HDSD. The contribution of perennial grasses to herbage mass declined with RP and seasonal grazing treatments. Frequency of perennial grasses was unaffected by grazing treatment but the number of perennial grass plants increased over time in RP and seasonal treatments. HDSD allowed maintenance of basal cover whereas bare ground increased with RP and seasonal treatments. Litter accumulated in NIL but this was associated with a decline in perennial basal cover. Seasonal grazing treatments did not provide an advantage over RP and there appeared to be no benefit from including phenology in management decisions. In contrast, HDSD resulted in a stable and productive grassland ecosystem, with stocking rate estimated at 78% greater than other treatments. These features offer a desirable mix for future industry adoption in the mid-north of South Australia.

scholarly journals Response of soil respiration and soil microbial biomass carbon and nitrogen to grazing management in the Loess Plateau, China

2019 ◽  
Author(s):  
Zhen Wang ◽  
Xiuli Wan ◽  
Mei Tian ◽  
Xiaoyan Wang ◽  
Junbo Chen ◽  
...  
Keyword(s):  
Microbial Biomass ◽  
Soil Microbial Biomass ◽  
Microbial Biomass Carbon ◽  
Warm Season ◽  
Cold Season ◽  
Grazing Management ◽  
Biotic Factors ◽  
Soil Microbial ◽  
Grazing Intensities ◽  
Seasonal Grazing

Abstract. Grassland covers more than a third of the earth's terrestrial surface. Grazing management can affect grassland carbon dynamics and soil microbial biomass, yet limited information is available on the effects of grassland management on carbon dioxide efflux and soil microbial biomass carbon (SMBC) and nitrogen (SMBN). During 2010 and 2011, soil respiration (Rs), SMBC, and SMBN, as well as different abiotic and biotic factors were measured after long term rotational grazing (nine years) on the grasslands of the semi-arid Loess Plateau, China. Grazing management included different grazing intensities and seasonal grazing patterns (in summer or winter). Stocking rates of 0, 2.7, 5.6, and 8.7 sheep ha−1 were used as grazing intensities, and warm-season grazing and cold-season grazing by sheep during summer and winter from 2010 to 2011 were used as grazing patterns. We hypothesized that the different seasonal grazing patterns and grazing intensities would affect Rs in a semi-arid grassland ecosystem. Our results indicated that grazing management significantly affected the rate of Rs, which supports our hypothesis. Grazing intensities tended to increase SMBC, but had no effect on SMBN. We also found that SMBC in cold season grazing plots was higher than that in the warm season grazing plots. However, variation in grazing patterns had little effect on SMBN. Furthermore, a structural equation model indicated that the aboveground biomass and soil microbial biomass were two important biotic factors that controlled Rs. Soil temperature (ST) and soil moisture (SM), which were affected by grazing intensity and patterns, were significant abiotic factors affecting Rs and soil microbial biomass. Our observations suggest that grazing management may change soil carbon sequestration rates in grassland ecosystems, because of changes in the aboveground plant and soil microbial biomass.

scholarly journals Modeling the Propagation of Flood Waves at the Mouth of the Comoé River in Grand-Bassam (South East of Côte d’Ivoire)

2021 ◽  
pp. 33-42
Author(s):  
Kouakou Hervé Kouassi ◽  
Zilé Alex Kouadio ◽  
Yao Alexis N’go ◽  
Berenger Koffi ◽  
Gla Blaise Ouédé
Keyword(s):  
At Risk ◽  
Cote D'ivoire ◽  
Satellite Images ◽  
High Water ◽  
Climatic Data ◽  
Return Periods ◽  
Maximum Frequency ◽  
Topographic Data ◽  
Flooded Areas ◽  
Flood Waves

This study was carried out in order to determine the areas at risk of flooding during high water periods at the mouth of the Comoé River in Grand-Bassam. The database is essentially made up of hydro-climatic data, satellite images and topographic data. According to the various criteria, the Weibull law was selected to estimate the maximum frequency flows. According to this law, the flows at the return periods of 2, 10, 50 and 100 years are respectively 634, 733, 781 and 797 m3 / s. The modeling results showed that the areas exposed to the risk of flooding are located near the Ouladine lagoon and the Ebrié lagoon at the mouth of the Comoé river. The extent of the floodplains varies with flooded areas of the order of 85.63 km²; 89.42 km²; 101.67 km²; 107.10 km² for the return periods of 2; 10; 50 and 100 years old.

Responses of calcareous grassland plant communities to changed seasonal grazing management: results of a 31 year study

2021 ◽  
pp. 126026
Author(s):  
Lucy E. Ridding ◽  
James M. Bullock ◽  
Kevin J. Walker ◽  
Clive Bealey ◽  
Richard F. Pywell
Keyword(s):  
Plant Communities ◽  
Grazing Management ◽  
Calcareous Grassland ◽  
Seasonal Grazing

The machine training in problems of satellite images’s processing

Metrologiya ◽  
2020 ◽  
pp. 15-37
Author(s):  
L. P. Bass ◽  
Yu. A. Plastinin ◽  
I. Yu. Skryabysheva
Keyword(s):  
Remote Sensing ◽  
Neural Networks ◽  
Computer Vision ◽  
Satellite Images ◽  
Vision Systems ◽  
Earth Remote Sensing ◽  
Practical Applications ◽  
Convolution Neural Networks ◽  
Computer Vision Systems ◽  
Trained Neural Network

Use of the technical (computer) vision systems for Earth remote sensing is considered. An overview of software and hardware used in computer vision systems for processing satellite images is submitted. Algorithmic methods of the data processing with use of the trained neural network are described. Examples of the algorithmic processing of satellite images by means of artificial convolution neural networks are given. Ways of accuracy increase of satellite images recognition are defined. Practical applications of convolution neural networks onboard microsatellites for Earth remote sensing are presented.

Multitemporal distribution analysis of Dodonaea viscosa (L.) Jacq. by remote sensing in Durango, Mexico

2020 ◽  
Vol 13 (8) ◽  
Author(s):  
Marco, A. Márquez-Linares ◽  
Jonathan G. Escobar--Flores ◽  
Sarahi Sandoval- Espinosa ◽  
Gustavo Pérez-Verdín
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Design Methodology ◽  
Supervised Classification ◽  
Satellite Images ◽  
Ground Cover ◽  
Distribution Analysis ◽  
Dodonaea Viscosa ◽  
Artificial Neural ◽  
Landsat Satellite

Objective: to determine the distribution of D. viscosa in the vicinity of the Guadalupe Victoria Dam in Durango, Mexico, for the years 1990, 2010 and 2017.Design/Methodology/Approach: Landsat satellite images were processed in order to carry out supervised classifications using an artificial neural network. Images from the years 1990, 2010 and 2017 were used to estimate ground cover of D. viscosa, pastures, crops, shrubs, and oak forest. This data was used to calculate the expansion of D. viscosa in the study area.Results/Study Limitations/Implications: the supervised classification with the artificial neural network was optimal after 400 iterations, obtaining the best overall precision of 84.5 % for 2017. This contrasted with the year 1990, when overall accuracy was low at 45 % due to less training sites (fewer than 100) recorded for each of the land cover classes.Findings/Conclusions: in 1990, D. viscosa was found on only five hectares, while by 2017 it had increased to 147 hectares. If the disturbance caused by overgrazing continues, and based on the distribution of D. viscosa, it is likely that in a few years it will have the ability to invade half the study area, occupying agricultural, forested, and shrub areas

Designing a coherent land registration system for rural Portugal

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Tiago NUNES ◽  
Miguel COUTINHO
Keyword(s):  
Satellite Images ◽  
Field Research ◽  
Digital Native ◽  
Web Based ◽  
Registration System ◽  
Land Registration ◽  
Daily Rate ◽  
Property Owners ◽  
Property Identification

After almost a century of several attempts to establish a coherent land registration system across the whole country, in 2017 the Portuguese government decided to try a new, digital native approach to the problem. Thus, a web-based platform was created, where property owners from 10 pilot municipalities could manually identify their lands’ properties using a map based on satellite images. After the first month of submissions, it became clear that at the current daily rate, it would take years to achieve the goal of 100% rural property identification across just the 10 municipalities. Field research during the first month after launch enabled us to understand landowners’ relationships with their land, map their struggles with the platform, and prototype ways to improve the whole service. Understanding that these improvements would still not be enough to get to the necessary daily rate, we designed, tested and validated an algorithm that allows us to identify a rural property shape and location without coordinates. Today, we are able to help both Government and landowners identify a rural property location with the click of a button.

Management of grazing systems

1989 ◽  
pp. 117-122 ◽  
Author(s):  
J. Hodgson
Keyword(s):  
Management Practices ◽  
Management Control ◽  
Grazing Management ◽  
Relative Importance ◽  
Stocking Rate ◽  
Pastoral Systems ◽  
Starting Point ◽  
Alternative Means ◽  
Grazing Systems ◽  
Stocking Rates

Recent assessments of the relative importance of stocking rate. stocking policy and grazing management on the output from pastoral systems are used as a starting point to argue the need for objective pasture assessments to aid control of livestock enterprises to meet production targets. Variations in stocking rates, stocking policy and other management practices all provide alternative means of control of pasture conditions which are the major determinants of pasture and animal performance. Understanding of the influence of pasture conditions on systems performance should provide a better basis for management control and for Communication between farmers, extension officers and researchers. Keywords: Stocking rate, pasture condition, pasture cover

Regular estimates of paddock pasture mass can improve profitability on New Zealand dairy farms

2015 ◽  
Vol 77 ◽  
pp. 29-34 ◽  
Author(s):  
P.C. Beukes ◽  
S. Mccarthy ◽  
C.M. Wims ◽  
A.J. Romera
Keyword(s):  
Supply And Demand ◽  
Grazing Management ◽  
Average Error ◽  
Value Proposition ◽  
Perfect Knowledge ◽  
Operating Profit ◽  
A Value ◽  
Main Driver ◽  
Imperfect Knowledge ◽  
Farm Scale

Paddock selection is an important component of grazing management and is based on either some estimate of pasture mass (cover) or the interval since last grazing for each paddock. Obtaining estimates of cover to guide grazing management can be a time consuming task. A value proposition could assist farmers in deciding whether to invest resources in obtaining such information. A farm-scale simulation exercise was designed to estimate the effect of three levels of knowledge of individual paddock cover on profitability: 1) "perfect knowledge", where cover per paddock is known with perfect accuracy, 2) "imperfect knowledge", where cover per paddock is estimated with an average error of 15%, 3) "low knowledge", where cover is not known, and paddocks are selected based on longest time since last grazing. Grazing management based on imperfect knowledge increased farm operating profit by approximately $385/ha compared with low knowledge, while perfect knowledge added a further $140/ha. The main driver of these results is the level of accuracy in daily feed allocation, which increases with improving knowledge of pasture availability. This allows feed supply and demand to be better matched, resulting in less incidence of under- and over-feeding, higher milk production, and more optimal post-grazing residuals to maximise pasture regrowth. Keywords: modelling, paddock selection, pasture cover

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