scholarly journals EXPLORATION OF LAND RESOURCES FOR ANALYSING THE SUITABILITY OF SELECTED CROPS IN AN ADMINISTRATIVE UNIT OF THRISSUR DISTRICT, KERALA

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 435-437
Author(s):  
K. Shyju ◽  
K. Kumaraswamy
Keyword(s):  
Agricultural Land ◽  
Land Suitability ◽  
Model Soil ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Administrative Unit ◽  
Elevation Model ◽  
United Nations Food ◽  
Physical And Chemical

<p><strong>Abstract.</strong> The fitness of land for a defined use is termed as land suitability. The aim of the study is to find the land suitability of for selected crops examining the indicators of land suitability. The study focuses on analysing suitability of agricultural crops in Pazhayannur Block of Thrissur District. Pazhayannur is the administrative unit (block) in the east of the Talapilli Taluk of Thrissur District in Kerala. The physical and chemical characteristics of the soils of Pazhayannur block like texture, depth, slope, erosion, pH, salinity and soil available primary nutrients (NPK), secondary nutrients and micronutrients are identified. The slope of the terrain using Cartosat-Digital Elevation Model, soil erosion, rainfall and land capability is analysed for suitability classification. Land suitability is studied for the selected crops like paddy, banana, coconut, and rubber. The weighted overlay analysis in GIS is adopted for the analysis. The parameters are weighted based on its class and its influence in suitability of specific crops. The results on agricultural land suitability for individual crops were divided into 5 categories according to the land suitability classification of the United Nations Food and Agriculture Organization (FAO). It is identified that Pazhayannur has potential for the cultivation of the selected crops. The crops show high suitability (S1) in minor proportion and moderate suitability (S2) is found in 30 percent and above and marginal suitability (S3) is noticed in lesser areas. There is few portion of land which is currently not suitable for cultivation (N1) because of its topographic limitations. The restricted areas of forest are permanently not suited for agriculture (N2).</p>

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Floods Risk Mapping and Assessing Vulnerability of Morang, Nepal

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background: The impact of flooding rises due to unplanned settlements, especially in developing countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household.Methods: This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding.Results: The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district.Conclusion: This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

scholarly journals Assessing the hydrological suitability of floodplains for species-rich meadow restoration: a case study of the Thames floodplain, UK

2007 ◽  
Vol 11 (1) ◽  
pp. 170-179 ◽  
Author(s):  
A. J. Duranel ◽  
M. C. Acreman ◽  
C. J. Stratford ◽  
J. R. Thompson ◽  
D. J. Mould
Keyword(s):  
Agricultural Land ◽  
Hydrological Regime ◽  
Grassland Restoration ◽  
Rating Curve ◽  
Groundwater Levels ◽  
Digital Elevation ◽  
Elevation Model ◽  
Autumn And Winter ◽  
Physical And Chemical

Abstract. The physical and chemical environment of a floodplain needs to be assessed to define conservation targets for restoring it to species-rich meadows from agricultural land. A straightforward technique, widely applicable by site managers for assessing the suitability of the hydrological and hydro-chemical regime of a floodplain for wet grassland restoration, has been tested by examining the feasibility of restoring plants characteristic of NVC MG4 and MG8 communities to the Castle Meadows, Wallingford (Oxfordshire, UK). Hydro-chemical suitability has been assessed by comparing phosphorus concentrations with species-rich meadows nearby. The flooding regime was estimated based on a rating curve and a digital elevation model and groundwater levels were measured monthly in dipwells and piezometers. The hydrological regime was then compared with published reference guidelines for communities of conservation interest. For the Castle Meadows, the maximum duration of flood events in autumn and winter exceeded MG4 and MG8 species requirements across half of the site, while the depth of the groundwater table in summer exceeded species requirements in the other half. It was shown that, depending on topography, MG5 or MG13 may be more realistic vegetation targets.

scholarly journals Mapping Floods Risk and Assessing Flood Vulnerability for Settlement Areas

2021 ◽  
Author(s):  
Pawan Thapa ◽  
Narayan Thapa
Keyword(s):  
Drainage Density ◽  
Google Earth ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Digital Elevation ◽  
Two Factors ◽  
Flooding Risk ◽  
Elevation Model ◽  
The One ◽  
The Impact

Abstract Background The impact of flooding rises due to unplanned settlements, especially in developing and underdeveloped countries. This study tries to address these issues by mapping flood risk places and assessing their impact on population and household. Methods This study used the dataset available in Google Earth Engine (GEE), Food and Agriculture Organization (FAO), Central Bureau Statistics (CBS), Earth Data for preparing slope, drainage density, digital elevation model, rainfall, land use map, and soil map. These maps create using GEE and QGIS through overlay analysis that has two factors. The one is influence and other slopes, and it has provided high and low value according to its role on flooding. Results The risk assessment shows around twenty-four percent population is at higher risk, whereas more than three thousand settlements are prone to flooding. It depicts a significant increasing trend of floods in the Morang district. Conclusion This settlement risk map can help determine the flood safe and very high-risk areas in the Morang district. It will support residential places' planning by the local government, urban planners, and community people to reduce flooding risk.

Agricultural waste as a source of innovative and compostable composite biopolymers for food packaging: a scientific review

2021 ◽  
Author(s):  
Anna Ronzano ◽  
Roberta Stefanini ◽  
Giulia Borghesi ◽  
Giuseppe Vignali
Keyword(s):  
Food Packaging ◽  
Agricultural Land ◽  
Raw Materials ◽  
Agricultural Waste ◽  
Natural Fibers ◽  
Scientific Review ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Regional Project ◽  
Materials Used

"The recovery of agriculture waste is one of the challenges of 2030 Agenda. Food and Agriculture Organization states that 30 % of the world’s agricultural land is used to produce food that is later lost or wasted, and the global carbon footprint corresponds to 7% of total greenhouse gases emissions. Alternatively, natural fibers contained in food and agricultural waste could be a valuable feedstock to reinforce composite biopolymers contributing to increase mechanical properties. In addition, the use of biopolymers matrix could contribute significantly to reduce the environmental footprint of the biobased compounds. Based on these premises, a regional project in Emilia-Romagna, aims to enhance agricultural waste to produce food packaging materials which in turn would contribute to the reduction of green raw materials used. This article reviews the state of art of composite biopolymers added with fillers extracted by food and agricultural waste, analyzing the literature published on scientific databases such as Scopus. The characteristics, advantages and drawbacks of each innovative sustainable material will be studied, trying to compare their various properties. The results of the work could guide companies in the choice of eco-sustainable packaging and lay the foundations for the development of the mentioned regional project."

scholarly journals Sustainable and Environmentally Friendly Essential Oils Extracted from Pineapple Waste

2021 ◽  
Vol 12 (5) ◽  
pp. 6833-6844
Keyword(s):  
Essential Oil ◽  
Essential Oils ◽  
Bioactive Compounds ◽  
Raw Material ◽  
Ananas Comosus ◽  
Pineapple Waste ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Aldehydes And Ketones ◽  
United Nations Food

Pineapple (Ananas comosus (L.) Merril), one of the major fruit crops, is mainly used for raw consumption and for industrial juice production, which creates large amounts of residues. The United Nations Food and Agriculture Organization (FAO) has estimated that pineapple waste accounts for between 50 to 65 % of the total weight of the fruit. Industrial pineapple waste is a major source of pollution as important quantities of primary residues are not further processed. Pineapple waste contains bioactive compounds such as carotenoids, polyphenols, fibers, vitamins, enzymes, and essential oils. These phytochemicals can be used in the food industry, medicine and pharmacy, textile, and others. This review highlights essential oil and other bioactive compounds extracted from pineapple waste and the composition of pineapple essential oil. Pineapple peels are the potential raw material for essential oil extraction through various methods. Modern spectrometric methods have shown that essential oil extracted from pineapple waste comprises esters, alcohols, aldehydes, and ketones. From this overview, it can be concluded that there is an important need for further research into pineapple waste as a potential source of valuable byproducts, as well as new techniques to studying industrial organic residuals to achieve higher recovery rates of valuable bioactive compounds used in pharmaceuticals, cosmetic and chemical industries as well as for developing new functional foods.

Distribution of Food in a Specialized Hospital Using Ambient Intelligence to Improve a Model of Macroergonomics

2019 ◽  
pp. 231-241
Author(s):  
Alberto Ochoa Zezzatti ◽  
Juan Luis Hernandez Arellano ◽  
Gilberto Rivera ◽  
Daniel Azpeitia ◽  
Luis Fernando Maldonado
Keyword(s):  
Decision Making ◽  
Latin American ◽  
Distribution System ◽  
Ambient Intelligence ◽  
Food Distribution ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Specialized Hospital ◽  
United Nations Food ◽  
Latin American Countries

SIDA (Intelligent Food Distribution System, for its acronym in Spanish) is a proposed tool for the distribution of food that can be personalized depending on the medical characteristics of each patient. The target of the tool is to provide foods that contain higher nutrients in the diet set by a hospital. A model of decision trees was based on data from the organization of the United Nations Food and Agriculture Organization (FAO) and used for decision making in the simulated three basic foods based on the diet of Latin American countries typically integrated by rice, potatoes, and lentils from the parameters of fat, energy, and protein, respectively, that contains every type of food.

scholarly journals Scale-Optimized Surface Roughness for Topographic Analysis

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 322 ◽  
Author(s):  
John B. Lindsay ◽  
Daniel R. Newman ◽  
Anthony Francioni
Keyword(s):  
Surface Roughness ◽  
Forest Cover ◽  
Agricultural Land ◽  
Spatial Scales ◽  
Grid Cell ◽  
Topographic Analysis ◽  
Digital Elevation ◽  
Locally Adaptive ◽  
Elevation Model

Surface roughness is a terrain parameter that has been widely applied to the study of geomorphological processes. One of the main challenges in studying roughness is its highly scale-dependent nature. Determining appropriate mapping scales in topographically heterogenous landscapes can be difficult. A method is presented for estimating multiscale surface roughness based on the standard deviation of surface normals. This method utilizes scale partitioning and integral image processing to isolate scales of surface complexity. The computational efficiency of the method enables high scale sampling density and identification of maximum roughness for each grid cell in a digital elevation model (DEM). The approach was applied to a 0.5 m resolution LiDAR DEM of a 210 km2 area near Brantford, Canada. The case study demonstrated substantial heterogeneity in roughness properties. At shorter scales, tillage patterns and other micro-topography associated with ground beneath forest cover dominated roughness scale signatures. Extensive agricultural land-use resulted in 35.6% of the site exhibiting maximum roughness at micro-topographic scales. At larger spatial scales, rolling morainal topography and fluvial landforms, including incised channels and meander cut banks, were associated with maximum surface roughness. This method allowed for roughness mapping at spatial scales that are locally adapted to the topographic context of each individual grid cell within a DEM. Furthermore, the analysis revealed significant differences in roughness characteristics among soil texture categories, demonstrating the practical utility of locally adaptive, scale-optimized roughness.

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