scholarly journals An Integrated Approach for Crop Production Analysis from Geographic Information System Data using SqueezeNet

2022 ◽  
Vol 3 (4) ◽  
pp. 308-321
Author(s):  
K. Geetha
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Crop Production ◽  
Integrated Approach ◽  
Geographic Information ◽  
Town Planning ◽  
Indian States ◽  
Gis Applications ◽  
Huge Impact ◽  
System Data

Predictions and estimations are very important for agriculture applications. The estimation results on crop production may have a huge impact in the economy of a country by changing their export and import data. The estimation of crop production was started by collecting information manually from the fields and analyzing it using a computer. However, the accuracy was not up to the mark due to the error caused by manual collection of data. The Geographic Information System (GIS) applications are developed to store the information observed from the satellite images on change detection in town planning, disaster management, business development and vegetation management. The proposed work estimates the crop production of Indian states from a GIS dataset with a SqueezeNet algorithm. The performance of the SqueezeNet algorithm is compared with the traditional Inception and ResNet algorithms.

Automatic Identification of Roadway Horizontal Alignment Information Using Geographic Information System Data: CurvS Tool

2021 ◽  
pp. 036119812110363
Author(s):  
Bekir Bartin ◽  
Sami Demiroluk ◽  
Kaan Ozbay ◽  
Mojibulrahman Jami
Keyword(s):  
Information System ◽  
New Jersey ◽  
Geographic Information System ◽  
Geographic Information ◽  
Automatic Identification ◽  
Web Based ◽  
Horizontal Alignment ◽  
System Data ◽  
Overlap Ratio ◽  
Geographic Information System Data

This paper introduces CurvS, a web-based tool for researchers and analysts that automatically extracts, visualizes, and analyzes roadway horizontal alignment information using readily available geographic information system roadway centerline data. The functionalities of CurvS are presented along with a brief background on its methodology. The validation of its estimation results are presented using actual horizontal alignment data from two different roadway types: Route 83, a two-lane two-way rural roadway in New Jersey and I-80, a freeway segment in Nevada. Different metrics are used for validation. These are identification rates of curved and tangent sections, overlap ratio of curved and tangent sections between estimated and actual horizontal alignment data, and percent fit of curve radii. The validation results show that CurvS is able to identify all the curves on these two roadways, and the estimated section lengths are significantly close to the actual alignment data, especially for the I-80 freeway segment, where 90% of curved length and 94% of tangent section length are correctly matched. Even when curves have small central angles, such as the ones in Route 83, CurvS’s estimations covers 71% of curved length and 96% of tangent section length.

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