Mapping Agewise Discrimination of Arecanut Crop Water Requirement Using Hyperspectral Remote Sensing

Bhojaraja, B. E.; Hegde, Gaurav; Umesh, Pruthviraj; Shetty, Amba; Nagaraj, M. K.

doi:10.1016/j.aqpro.2015.02.186

Cited by 10 publications

(4 citation statements)

References 6 publications

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“…Also, in Guangzhou, litchi crops were categorized in this way. Using the Hyperion data, the Spectral Angular Mapper (SAM) classifier was used to categorize crops in the Karnataka region [36].…”

Section: Literature Reviewmentioning

confidence: 99%

Remote Sensing and Decision Support System Applications in Precision Agriculture: Challenges and Possibilities

Mehedi,

Hanif,

Bilal

et al. 2024

IEEE Access

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As the world's population rises, there will be a greater need for food, which will have repercussions on the environment and on crop yields. Increased production, efficient resource allocation, climate change adaptation, and diminished food waste are the four cornerstones of Agriculture 4.0's vision for the future of farming. Agriculture 4.0 makes use of cutting-edge data systems and Internet technology to acquire, analyze, and organize massive amounts of farming facts such as weather reports, soil conditions, market demands, and land usage to better guide farmers' decisions and boost their bottom lines. As a result, research on agricultural decision support systems for Agriculture 4.0 has gained significant momentum. Crop monitoring and yield forecasting are two applications where remote sensing has proven useful, and these two areas are intrinsically linked to variations in soil, weather, and biophysical and biochemical factors. Multi-and hyper-spectral data, radar, and lidar imaging are just some of the remote tools that could be employed for crop monitoring and yield forecasting. This paper's goal is to examine some of the difficulties that can arise in the future while using agricultural decision-support platforms in the context of Agriculture 4.0. Addressing these identified obstacles may help future researchers create better decisionassistance systems. This research examines the possibilities, benefits, and drawbacks of each method, as well as how well they work in various agricultural settings. Furthermore, these methods are demonstrated in a variety of strategies that can be effectively employed. In this research, we take a look at some remote sensing techniques developed to increase farm profits while minimizing their impact on the natural world. This research shows how remote sensing information can be used to predict crop yields, evaluate plant nutrient needs and soil nutrient levels, calculate plant moisture levels, and manage weed populations, among other applications.

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Section: Literature Reviewmentioning

confidence: 99%

Remote Sensing and Decision Support System Applications in Precision Agriculture: Challenges and Possibilities

Mehedi,

Hanif,

Bilal

et al. 2024

IEEE Access

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“…In the following Table 3, the crop coefficient and length of the growing period for each of the considered crops are presented. Hence, according to many researchers, e.g., [46][47][48], the equations recommended by FAO [45] to compute current irrigation requirements are summarized from equation (1) through equation ( 3) as follows:…”

Section: Agronomy Datamentioning

confidence: 99%

Estimation of Current Water Use over the Complex Topography of the Nile Basin Headwaters: The Case of Ghba Subbasin, Ethiopia

Hiben

Awoke

Ashenafi

2022

Advances in Civil Engineering

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Quantifying the available and useable water is critical work in any water resource study and design project. However, it is challenging to provide a robust and accurate estimation of water use and distribution for better water resource management and planning. This study aims to estimate the water use by different sectors, including water supply and irrigation sectors, by adopting estimated demand and supply water quantity. The current total population of the subbasin has been estimated to be 1.21 million. Thus, in the subbasin, current water use is estimated as follows: domestic and nondomestic water use in the rural area is 3.5 Mm3/year and 0.174 Mm3/year, respectively. The domestic water use of the towns is 12.77 Mm3/year. The industrial water use of the urban areas is 21.2 Mm3/year, whereas the commercial, public, and institutional water use are 1.87 Mm3/year. The real loss for all the water supply uses is 7.8 Mm3/year. Thus, the total current water supply uses are about 47.225 Mm3/year. From the existing irrigation schemes, about 10,254.8 ha areas are irrigated by both smallholders and different investors, growing vegetables, cereals, and fruit trees. The annual irrigation water requirements of these schemes are computed to be 151.55 Mm3. Livestock water demand of the subbasin was assessed and estimated based on the population and consumption rates of the species. Currently, the subbasin has a total livestock population of 1,527,835, and the water demand of which is estimated at 5.3 Mm3 per annum. Hence, the total current water use estimate of the subbasin is 204.1 Mm3.

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“…After calculating the actual evapotranspiration, the total CWR is measured through the soil water balance of the system . Table summarizes different formulas suggested in the literature for calculating the CWR with their effective parameters.…”

Section: Greenhouse Technologymentioning

confidence: 99%

“…104,[106][107][108] After calculating the actual evapotranspiration, the total CWR is measured through the soil water balance of the system. 59,105,[107][108][109][110][111] Table 4 summarizes different formulas suggested in the literature for calculating the CWR with their effective parameters. An example of this calculation for different crops is presented in Sawant et al 105 which shows that the reference evapotranspiration is 0.00319 to 0.00481 m 3 /d/m 2 and the total CWR is 0.001 to 0.0043 m 3 /d/m 2 .…”

Section: Greenhouse's Crop Water Requirementmentioning

confidence: 99%

A comprehensive review of solar‐driven desalination technologies for off‐grid greenhouses

Shekarchi

Shahnia

2018

Int J Energy Res

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Summary This paper is motivated by the crisis of freshwater in remote areas around the world and responds to the growing need for sustainable food production in arid lands. It focuses on utilizing solar energy to yield freshwater from the sea or brackish water with less environmental impacts, for greenhouses, which can produce sustainable food all over the year. The integration of various solar‐driven desalinations such as solar still, humidification‐dehumidification, reverse osmosis, electrodialysis, and multieffect and multistage flash with greenhouses are evaluated, for better sustainability towards greenization. The paper first discusses the specifications of solar‐driven desalinations and compares their advantages and limitations. Then, different types of greenhouses are introduced, and their total water requirement is discussed based on their locations, crop type, greenhouse technology, irrigation type, and environmental conditions, as well as their cooling and heating strategies. Later, the existing integration of solar‐driven desalinations with greenhouses are reviewed, and their advantages and limitations are deliberated. Finally, the paper discusses the criteria to be considered when selecting solar‐driven desalinations for greenhouses and presents a detailed comparison between the water production rate and cost as well as the energy consumption of these systems. In the end, the most appropriate combinations of solar‐driven desalinations with greenhouses are recommended based on their water requirement and production cost.

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Mapping Agewise Discrimination of Arecanut Crop Water Requirement Using Hyperspectral Remote Sensing

Cited by 10 publications

References 6 publications

Remote Sensing and Decision Support System Applications in Precision Agriculture: Challenges and Possibilities

Remote Sensing and Decision Support System Applications in Precision Agriculture: Challenges and Possibilities

Estimation of Current Water Use over the Complex Topography of the Nile Basin Headwaters: The Case of Ghba Subbasin, Ethiopia

A comprehensive review of solar‐driven desalination technologies for off‐grid greenhouses

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