亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

An improved phenology-based CASA model for estimating net primary production of forest in central China based on Landsat images

每年落叶的 初级生产 物候学 常绿 环境科学 归一化差异植被指数 大气科学 生长度日 生物量(生态学) 植被(病理学) 均方误差 林业 自然地理学 生态学 气候变化 数学 统计 地理 生态系统 生物 地质学 医学 病理
作者
Yanyan Pei,Jinliang Huang,Lihui Wang,Hong Chi,Yajie Zhao
出处
期刊:International Journal of Remote Sensing [Taylor & Francis]
卷期号:39 (21): 7664-7692 被引量:35
标识
DOI:10.1080/01431161.2018.1478464
摘要

The optimum temperature () in the current Carnegie–Ames–Stanford Approach (CASA) model was defined as the mean temperature of the month when normalized difference vegetation index (NDVI) reaches its maximum. However, it requires improvements from a comprehensive perspective due to that the stability of the maximum NDVI acquisition is subjected to a variety of factors. The article proposed an improved CASA model by redefining the optimum temperature based on phenology () to model the net primary production (NPP) of forest in Shennongjia, central China, and analysed the relationship between annual mean NPP and topography. Logistic function was used to model the phenological phases of forest and was redefined as the mean temperature during the period of maturity stability. The improved was lower than the for five forest types. Specifically, the average of evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest, deciduous needleleaf forest, and mixed forest were 22.72°C, 23.31°C, 24.05°C, 23.41°C, and 23.18°C, respectively, whereas the corresponding average were 24.42°C, 24.90°C, 24.54°C, 24.57°C, and 24.43°C, respectively. The NPP observations transformed from field measured biomass were used to evaluate the accuracy of NPP estimated from the -based CASA model and the -based CASA model. The result indicated that the accuracy of the -based CASA model was higher than that of the -based CASA model, with the coefficients of determination of 0.837 (root mean square error (RMSE) = 75 g C m–2 year–1) and 0.632 (RMSE = 122 g C m–2 year–1), respectively. The total NPP of forest in Shennongjia modelled by the -based CASA model and the -based CASA model were 1.40 and 1.35 Tg C year–1, respectively. The relationship between the annual mean NPP and altitude showed a quadratic polynomial function at the altitude from 500 to 3000 m, while the relationship between the annual mean NPP and aspect showed a sine function when aspect in the range of 4.5–360.0°. The results demonstrate that the improvement of CASA model (-based CASA model) is of great significance in phenology and plays as a promising alternative method to model NPP for forest.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
潘啊潘完成签到 ,获得积分10
刚刚
橙子发布了新的文献求助10
3秒前
小马甲应助deway采纳,获得10
13秒前
赘婿应助科研通管家采纳,获得10
19秒前
科研通AI2S应助科研通管家采纳,获得10
19秒前
21秒前
deway发布了新的文献求助10
26秒前
Hello应助1234采纳,获得10
26秒前
27秒前
xaogny发布了新的文献求助10
30秒前
所所应助小宝采纳,获得10
35秒前
44秒前
46秒前
小宝发布了新的文献求助10
47秒前
NexusExplorer应助橙子采纳,获得50
53秒前
56秒前
上官若男应助deway采纳,获得10
59秒前
1分钟前
爆米花应助辞树采纳,获得10
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
last123发布了新的文献求助10
1分钟前
goodltl完成签到 ,获得积分10
1分钟前
1分钟前
1分钟前
小债完成签到,获得积分10
1分钟前
1分钟前
deway发布了新的文献求助10
1分钟前
1分钟前
1分钟前
Nancy发布了新的文献求助10
1分钟前
2分钟前
2分钟前
2分钟前
sherrt发布了新的文献求助10
2分钟前
顾矜应助科研通管家采纳,获得10
2分钟前
CipherSage应助科研通管家采纳,获得10
2分钟前
2分钟前
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
Zeolites: From Fundamentals to Emerging Applications 1500
Architectural Corrosion and Critical Infrastructure 1000
Early Devonian echinoderms from Victoria (Rhombifera, Blastoidea and Ophiocistioidea) 1000
Hidden Generalizations Phonological Opacity in Optimality Theory 1000
Handbook of Social and Emotional Learning, Second Edition 900
translating meaning 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 4917906
求助须知:如何正确求助?哪些是违规求助? 4190803
关于积分的说明 13015343
捐赠科研通 3960435
什么是DOI,文献DOI怎么找? 2171259
邀请新用户注册赠送积分活动 1189298
关于科研通互助平台的介绍 1097514