High-resolution satellite imagery to assess orchard characteristics impacting water use

遥感 果园 环境科学 卫星图像 阈值 灌溉 分水岭 卫星 水文学(农业) 计算机科学 地理 人工智能 地质学 岩土工程 航空航天工程 园艺 工程类 生物 生态学 机器学习 图像(数学)
作者
Pierre Rouault,Dominique Courault,Fabrice Flamain,Guillaume Pouget,Claude Doussan,Raúl López‐Lozano,Matthew F. McCabe,Marta Debolini
出处
期刊:Agricultural Water Management [Elsevier BV]
卷期号:295: 108763-108763 被引量:8
标识
DOI:10.1016/j.agwat.2024.108763
摘要

Most Orchards throughout the Mediterranean basin rely heavily on irrigation, a dependency increasing due to climate changes. Assessing the water requirement (WR) is crucial and depends on different factors, including orchard age, tree density per field, inter-row management. This study proposes new methods to evaluate these characteristics with remote sensing (RS). Various remote sensors providing high and very high spatial resolution images are investigated and their accuracy is assessed. The final objective is to assess WR using variables derived from remote sensing compared to data provided by water managers and from the FAO method. A typical Mediterranean watershed was selected in South-Eastern France, with orchards having various agricultural practices. Original methods were developed with Sentinel 2 (S2) data (2016–2023), 1 Pleiades image (2022) and the extraction of Google-satellite-hybrid images (GSH, 2017), and assessed using a large ground observation dataset (information on water use collected on 366 fields). Five orchards were monitored by capacitive sensors to assess the water balance. Irrigation durations ranged from 3–300 hours/year, with decision influenced by tree density and plot age. To identify young orchards, a thresholding approach on S2 derived NDVI effectively identified young orchards achieving a 98% accuracy rate. Grassed and non-grassed orchards were mapped using two methods, with a random forest classification using three spectral bands with 72% accuracy and a supervised approach yielding 81% accuracy for GSH and 57% for Pleiades. The performance depends on the acquisition date of images. A pattern detection algorithm applied to GSH and Pleaides determined tree density, showing a high correlation (r²=0.9) with observed data. These RS derived variables allowed to compute orchard water requirements at the watershed scale, ranging from 70 to 550 mm annually depending on management practices. The proposed methods can be extrapolated to other territories and are implemented using open access softwares.
最长约 10秒,即可获得该文献文件

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
11111111发布了新的文献求助10
1秒前
睡觉踢被子完成签到 ,获得积分10
1秒前
haoliang发布了新的文献求助10
2秒前
在水一方的应助被ww采纳,获得10
2秒前
干净的雅青完成签到,获得积分10
3秒前
领导范儿的应助被wewldsldsk采纳,获得10
6秒前
7秒前
体贴的觅珍关注了科研通微信公众号
7秒前
奈何完成签到,获得积分10
8秒前
奥丑拉唑发布了新的文献求助10
10秒前
10秒前
女青年完成签到,获得积分10
11秒前
随风发布了新的文献求助10
12秒前
loii的应助被久怨采纳,获得50
12秒前
14秒前
隐形曼青的应助被zy0411采纳,获得10
14秒前
寻月完成签到,获得积分10
14秒前
15秒前
李欣桦发布了新的文献求助10
15秒前
阳菲发布了新的文献求助20
16秒前
脑洞疼的应助被july7292采纳,获得10
16秒前
16秒前
17秒前
Jasper的应助被haoliang采纳,获得10
18秒前
夏染给夏染的求助进行了留言
18秒前
bioxtt完成签到,获得积分10
18秒前
11111111发布了新的文献求助10
19秒前
Akim的应助被shuitian998采纳,获得10
19秒前
杭啊发布了新的文献求助10
20秒前
呜呜呜啦完成签到,获得积分10
21秒前
ww发布了新的文献求助10
21秒前
研友_VZG7GZ的应助被july7292采纳,获得10
22秒前
xz完成签到,获得积分20
22秒前
乐空思的应助被W星球Y族人采纳,获得200
22秒前
今后的应助被天真怜晴采纳,获得10
23秒前
23秒前
24秒前
JSM完成签到,获得积分10
25秒前
Viper完成签到,获得积分10
27秒前
28秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Production Logging: Theoretical and Interpretive Elements 400
CLSI C56QG Examples of Hemolyzed, Icteric, and Lipemic/Turbid Samples Quick Guide 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7817426
求助须知:如何正确求助?哪些是违规求助? 9346087
关于积分的说明 20533428
捐赠科研通 7409937
什么是DOI,文献DOI怎么找? 3331728
关于科研通互助平台的介绍 2478103
邀请新用户注册赠送积分活动 2351350