Optimized Data Mining Techniques for Outlier Detection, Removal, and Management Zone Delineation for Yield Prediction

2020 ◽  
pp. 222-258
Author(s):  
Roopa G. M. ◽  
Arun Kumar G. H. ◽  
Naveen Kumar K. R. ◽  
Nirmala C. R.
Keyword(s):  
Outlier Detection ◽  
Spatial Data ◽  
Crop Management ◽  
Vital Role ◽  
Soil Parameters ◽  
Management Zone ◽  
Field Patterns ◽  
Free Data ◽  
Spatial Attributes ◽  
Data Context

Enormous agricultural data collected using sensors for crop management decisions on spatial data with soil parameters like N, P, K, pH, and EC enhances crop growth for soil type. Spatial data play vital role in DSS, but inconsistent values leads to improper inferences. From EDA, few observations involve outliers that deviates crop management assessments. In spatial data context, outliers are the observations whose non-spatial attributes are distinct from other observations. Thus, treating an entire field as uniform area is trivial which influence the farmers to use expensive fertilizers. Iterative-R algorithm is applied for outlier detection to reduce the masking/swamping effects. Outlier-free data defines interpretable field patterns to satisfy statistical assumptions. For heterogeneous farms, the aim is to identify sub-fields and percentage of fertilizers. MZD achieved by interpolation technique predicts the unobserved values by comparing with its known neighbor-points. MZD suggests the farmers with better knowledge of soil fertility, field variability, and fertilizer applying rates.

scholarly journals Optimization for prediction model of palm oil land suitability using spatial decision tree algorithm

2020 ◽  
Vol 8 (3) ◽  
pp. 192-200
Author(s):  
Andi Nurkholis ◽  
Imas Sukaesih Sitanggang
Keyword(s):  
Decision Tree ◽  
Palm Oil ◽  
Land Use Planning ◽  
Spatial Data ◽  
Vital Role ◽  
Exchange Capacity ◽  
Land Suitability ◽  
Decision Tree Algorithm ◽  
Spatial Join ◽  
Tree Algorithm

Land suitability evaluation has a vital role in land use planning aimed to increase food production effectiveness. Palm oil is a leading and strategic commodity for Indonesian people, which is predicted consumption will exceed production in the future. This study aims to evaluate palm oil land suitability using a spatial decision tree algorithm that is conventional decision tree modification for spatial data classification with adding spatial join relation. The spatial dataset consists of eight explanatory layers (soil nature and characteristics), and a target layer (palm oil land suitability) in Bogor District, Indonesia. This study produced three models, where the best model was obtained based on optimizing accuracy (98.18 %) and modeling time (1.291 seconds). The best model has 23 rules, soil texture as the root node, two variables (drainage and cation exchange capacity) are uninvolved, with land suitability visualization obtains percentage S2 (29.94 %), S3 (53.16 %), N (16.57 %), and water body (0.33 %).

scholarly journals A Greenhouse Monitoring and Crop Prediction System Implemented using Iot, Arduino Uno and Nodemcu

2020 ◽  
Vol 8 (4S5) ◽  
pp. 1-4
Keyword(s):  
Soil Moisture ◽  
Vital Role ◽  
Soil Parameters ◽  
Prediction System ◽  
Greenhouse Soil ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Arduino Uno ◽  
Environment Parameters ◽  
Modern Technologies

IoT plays a vital role in modern technologies by connecting objects to internet through which real time values can be . The system is developed using one such technology in greenhouse. The system developed for the purpose of crop prediction in greenhouse. Soil parameters such as pH and moisture, the environment parameters like temperature and humidity is acquired from the implemented system. The required nutrients such as N, P, K is fed to the crops manually is also considered as input for crop prediction. The system is developed with Arduino Uno, NodeMCU ESP8266(WIFI Module), Sensor like DHT Humidity and Temperature DHT11, pH Analogy, Soil Moisture sensor, 12V DC motor for triggering, 12V Relay and a few other components to complete the circuit. Web hosting is done using PHP. The sensors values get stored in data base using MYSQL for further analytics.

Robust outlier detection in geo-spatial data based on LOLIMOT and KNN search

2021 ◽  
Author(s):  
Mohammadreza Tabatabaei ◽  
Roohollah Kimiaefar ◽  
Alireza Hajian ◽  
Alireza Akbari
Keyword(s):  
Outlier Detection ◽  
Spatial Data ◽  
Knn Search

Neighborhood Rough-Sets-Based Spatial Data Analytics

2018 ◽  
pp. 1835-1844
Author(s):  
Sharmila Banu K. ◽  
B. K. Tripathy
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Spatial Data ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Equivalence Classes ◽  
Continuous Data ◽  
Spatially Correlated ◽  
Spatial Attributes ◽  
Neighborhood Rough Sets

Rough Set Theory partitions a universe using single layered granulation. The equivalence classes induced by rough sets are based on discretised values. Considering the fact that the spatial data are continuous at large, discretising them may cause loss of data. Neighborhood approximations can lead to closely related coverings using continuous values. Besides, the spatial attributes also need to be given due consideration and should be handled unlike non-spatial attributes in the process of dimensionality reduction. This chapter analyses the use of Neighborhood rough sets for continuous data and handling spatially correlated attributes using rough sets.

GIS-Based Decision Support System for Village Level

2018 ◽  
pp. 275-295
Author(s):  
Subbu Lakshmi Esakki Pandian ◽  
Kiran Yarrakula ◽  
Probal Chaudhury
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Spatial Data ◽  
Rural Areas ◽  
Vital Role ◽  
Population Total ◽  
Rural Sector ◽  
Male And Female ◽  
Village Level

Decision support system (DSS) plays a vital role especially in rural areas to develop rural sector for sustainable development and socio-economic uplifting of the country. To make appropriate decisions and to develop village economy, decision support system is useful for the mandal revenue officer, collector, Surpanch, and different administrators. It deals both spatial and non-spatial data at village level and comprises various ancillary information including mandal maps and village-wise information of Anantapur and Kadapa districts of Andhra Pradesh such as number of houses, male and female, SC/ST/OBC/general (or) OC population, literate and illiterate population, total working and non-working population. Datasets are collected from district collector office, mandal revenue officer (MRO) and inserted in GIS database. This chapter makes an attempt to build features of various decisions at Anantapur and Kadapa districts by integrating various layers of information at village level.

Digitalizing and Geo-Enabling Observation Cards to Improve Hazard Mitigation and Better Risk Assessment

2021 ◽  
Author(s):  
P. E. Paramitha
Keyword(s):  
Risk Assessment ◽  
Spatial Data ◽  
Mobile Application ◽  
Occupational Safety ◽  
Oil And Gas ◽  
Hazard Mitigation ◽  
Oil And Gas Industry ◽  
Vital Role ◽  
Gas Industry ◽  
Field Workers

Health, safety, and environment (HSE) play a vital role and sits at the highest pedestal in the oil and gas industry. It should therefore be the top priority in the oil and gas industry as this function enables a reduction in potential hazards, including injuries, fatalities, damage to facilities, and occupational safety. Field workers typically use observation cards to report the potential hazards or discrepancies discovered in the field. However, in some companies, reporting is still done manually by filling out the observation cards in handwritten paper form and then manually submitted to the HSE supervisor. The supervisor will receive all the forms, input the data into spreadsheets, analyze the data, then make decisions to mitigate the hazard(s). These workflows are certainly time-consuming and prone to errors. Therefore, this paper aims to simplify these workflows by enabling digital system of records and geospatial information on HSE observation. Geographic Information System (GIS) form-based mobile application that integrates object location, mobile phone camera, and textual information was developed. In this paper, a GIS digital-based form that connects spatial data with attribute data is presented. Field workers can use this form to report any potential hazards and acquired pictures of evidence using mobile devices. The report will be transmitted to the server database through a web service, being visualized and analyzed to alert the potential hazards for pro-active action. In addition, this GIS form-based mobile application can also be used in a web-based application for office workers. This application will reduce errors while filling the observation cards or adding the data to sheets manually. It also time-efficient since the submitted reports can be monitored in real-time, and the follow-up action can be executed sooner. This will provide easier accessibility and better experience of hazard reporting anytime and anywhere, improve hazard mitigation, and better risk assessment.

scholarly journals Abundance and Diversity of Soybean-Nodulating Rhizobia in Black Soil Are Impacted by Land Use and Crop Management

2014 ◽  
Vol 80 (17) ◽  
pp. 5394-5402 ◽  
Author(s):  
Jun Yan ◽  
Xiao Zeng Han ◽  
Zhao Jun Ji ◽  
Yan Li ◽  
En Tao Wang ◽  
...  
Keyword(s):  
Land Use ◽  
Bradyrhizobium Japonicum ◽  
Crop Management ◽  
Black Soil ◽  
Soil Parameters ◽  
Available Phosphorus ◽  
Content Type ◽  
Rhizobial Diversity ◽  
Abundance And Diversity ◽  
Effects Of Land Use

ABSTRACTTo investigate the effects of land use and crop management on soybean rhizobial communities, 280 nodule isolates were trapped from 7 fields with different land use and culture histories. Besides the knownBradyrhizobium japonicum, three novel genospecies were isolated from these fields. Grassland (GL) maintained a higher diversity of soybean bradyrhizobia than the other cultivation systems. Two genospecies (Bradyrhizobiumspp. I and III) were distributed widely in all treatments, whileBradyrhizobiumsp. II was found only in GL treatment. Cultivation with soybeans increased the rhizobial abundance and diversity, except for the soybean monoculture (S-S) treatment. In monoculture systems, soybeans favoredBradyrhizobiumsp. I, while maize and wheat favoredBradyrhizobiumsp. III. Fertilization decreased the rhizobial diversity indexes but did not change the species composition. The organic carbon (OC) and available phosphorus (AP) contents and pH were the main soil parameters positively correlated with the distribution ofBradyrhizobiumspp. I and II andBradyrhizobium japonicumand negatively correlated withBradyrhizobiumsp. III. These results revealed that different land uses and crop management could not only alter the diversity and abundance of soybean rhizobia, but also change interactions between rhizobia and legume or nonlegume plants, which offered novel information about the biogeography of rhizobia.

scholarly journals Exploring the Influence of Social Infrastructure on Experiences of Aging in Place in Dublin, Ireland

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 684-685
Author(s):  
Hannah Grove
Keyword(s):  
Older People ◽  
Inner City ◽  
Spatial Data ◽  
Aging In Place ◽  
Vital Role ◽  
Social Infrastructure ◽  
Daily Lives ◽  
Analysis Techniques ◽  
Data Collection And Analysis ◽  
Different Types

Abstract This paper presents results from a PhD project that has carried out interviews, mapping exercises and ‘go-along’ interviews with thirty-four people aged sixty-six and over, in an inner city and suburban study area within Dublin, Ireland. A key objective of this research was to identify places, activities and interactions of most importance to older people. Through qualitative and spatial data collection and analysis techniques, different types of ‘social infrastructure’ that individuals value and engage with, as part of their daily lives, are identified and presented using annotated maps. The interactions and types of activities that occur in these places, and why they are important, are also discussed. Results demonstrate the benefits of high quality social infrastructure (and the challenges associated with a lack of social infrastructure) through participant’s own experiences, and highlight the vital role this plays in supporting older people to age well in place.

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