Using the UAV-derived NDVI to evaluate spatial and temporal variation of crop phenology atcrop growing season in South Korea

归一化差异植被指数 物候学 环境科学 生长季节 遥感 作物 植被(病理学) 空间变异性 地理 叶面积指数 农学 林业 数学 统计 生物 病理 医学
作者
Dong‐Ho Lee,Jin-Ki Park,Kyong-Ho Shin,Jong-Hwa Park
标识
DOI:10.1117/12.2324959
摘要

In recent years, climate change and other anthropogenic factors have contributed to increased crop blight and harmful insects in South Korea crop fields. The main objective of this research was to develop an integrated method and procedure that can be used by unmanned aerial vehicle (UAV) to derive reliable, cost-effective, timely, and repeatable farm information on agricultural production of the field crop at regional level prior to the harvesting date. An attempt has been made in this study to investigate the role of geo-informatics to discriminate different crops at various levels of classification and monitoring crop growth. This research focuses on the evaluation of spatial and temporal variations in crop phenology at Chungbuk using the UAV image data. Crop canopy spectral data in the growing seasons were measured. UAV imagery combined with Smart Farm Map (SFM) were suggested as promising for use in a national crop monitoring system. The test bed area which located in Cheongju were observed by four bands of UAV mounted sensors. UAV images were acquired 6 times from May 6 to October 15, 2016. The difference of normalized difference vegetation index (NDVI) was analyzed. Results showed that NDVI of UAV were strongly correlated with vegetation vigor and growth. The spatial and temporal NDVI and land use and Land cover (LULC) distribution of the crop field were mapped based on the 4-band combination of UAV imagery. The results of this study, we found that the spatial and temporal variation and correlation with crop phenology, LULC classification, and NDVI relationship. The developed model in this study shows a promising result, which can be useful for forecasting crop vegetation conditions in regional scales. Also, the results suggest that the necessary classification performance can be obtained in most of the phenology at crop growing cases, therefore the analysis could be cost effective. The investment to achieve this seems to be worthwhile.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
冯明伟发布了新的文献求助10
1秒前
小马发布了新的文献求助30
2秒前
隐形的哈密瓜完成签到 ,获得积分10
2秒前
3秒前
4秒前
田様应助An采纳,获得30
4秒前
5秒前
叫滚滚发布了新的文献求助20
6秒前
李伽绘发布了新的文献求助10
8秒前
丘比特应助十九采纳,获得10
8秒前
8秒前
乐乐应助幽默的沁采纳,获得10
8秒前
所所应助HI采纳,获得10
9秒前
袋鼠完成签到,获得积分10
10秒前
10秒前
10秒前
10秒前
10秒前
随心发布了新的文献求助10
11秒前
Owen应助xiaoX12138采纳,获得10
11秒前
12秒前
12秒前
13秒前
13秒前
13秒前
华仔应助xls采纳,获得10
13秒前
科研人完成签到,获得积分10
13秒前
超级的晓槐完成签到,获得积分10
14秒前
舒服的尔蓝完成签到,获得积分10
14秒前
15秒前
torjain发布了新的文献求助10
16秒前
16秒前
16秒前
科目三应助BGWZSG采纳,获得10
16秒前
16秒前
17秒前
淡定的初夏应助袋鼠采纳,获得40
17秒前
17秒前
peng123发布了新的文献求助10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organic Reactions, Volume 116 1500
VALIDATION OF THE TAYLOR, ALAMEL AND VPSC MODELS FOR PLASTIC ANISOTROPY MODELING OF SHEET METALS 1000
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Machine Learning for Asset Management and Pricing 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7405806
求助须知:如何正确求助?哪些是违规求助? 9010349
关于积分的说明 19188900
捐赠科研通 7039142
什么是DOI,文献DOI怎么找? 3232181
关于科研通互助平台的介绍 2394322
邀请新用户注册赠送积分活动 2214241