Assessment of Carbon Sequestration Capacity of E. ulmoides in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6

被引:8
作者
Wang, Juan [1 ,2 ]
Wei, Xinxin [1 ,3 ,4 ]
Sun, Shuying [3 ]
Li, Minhui [3 ,4 ]
Shi, Tingting [1 ]
Zhang, Xiaobo [1 ]
机构
[1] China Acad Chinese Med Sci, Natl Resource Ctr Chinese Mat Med, State Key Lab Qual Ensurance & Sustainable Use Dao, Beijing 100700, Peoples R China
[2] Changchun Univ Chinese Med, Sch Pharmaceut Sci, Changchun 130117, Peoples R China
[3] Inner Mongolia Univ, Sch Life Sci, Hohhot 010070, Peoples R China
[4] Inner Mongolia Tradit Chinese & Mongolian Med Res, Hohhot 010010, Peoples R China
关键词
E; ulmoides; GF-6; WFV; red-edge band; random forest; net primary productivity; ecological suitability; NET PRIMARY PRODUCTION; MAXENT; CLASSIFICATION; VEGETATION; MODEL;
D O I
10.3390/s23187895
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Eucommia ulmoides Oliver. (E. ulmoides) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides. In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides, making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM-2<middle dot>a(-1). The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides, highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides.
引用
收藏
页数:21
相关论文
共 49 条
[1]   Assessing the niche of Rhododendron arboreum using entropy and machine learning algorithms: role of atmospheric, ecological, and hydrological variables [J].
Anand, Akash ;
Srivastava, Prashant K. ;
Pandey, Prem C. ;
Khan, Mohammed L. ;
Behera, Mukund D. .
JOURNAL OF APPLIED REMOTE SENSING, 2022, 16 (04)
[2]   Influence of Seasonal Air-Sea Interaction on the Interannual Variation of the NPP of Terrestrial Natural Vegetation in China [J].
Bai, Hui ;
Xiao, Fengjin ;
Zhang, Guo ;
Liu, Qiufeng ;
Qin, Yun ;
Liao, Yaoming .
ATMOSPHERE, 2022, 13 (11)
[3]   Searching for ecology in species distribution models in the Himalayas [J].
Bobrowski, Maria ;
Weidinger, Johannes ;
Schwab, Niels ;
Schickhoff, Udo .
ECOLOGICAL MODELLING, 2021, 458
[4]  
Chu Z., 2022, J. Chin. Urban For, V20, P126
[5]   An improved method to construct basic probability assignment based on the confusion matrix for classification problem [J].
Deng, Xinyang ;
Liu, Qi ;
Deng, Yong ;
Mahadevan, Sankaran .
INFORMATION SCIENCES, 2016, 340 :250-261
[6]  
Deyi Xiong, 2004, Natural Language Processing - IJCNLP 2004. First International Joint Conference. Revised Selected Papers (Lecture Notes in Artificial Intelligence Vol. 3248), P537
[7]  
Duan Q., 2020, For. Inventory Plan, V47, P133
[8]   Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery [J].
Fang, Peng ;
Yan, Nana ;
Wei, Panpan ;
Zhao, Yifan ;
Zhang, Xiwang .
REMOTE SENSING, 2021, 13 (14)
[9]   GLOBAL NET PRIMARY PRODUCTION - COMBINING ECOLOGY AND REMOTE-SENSING [J].
FIELD, CB ;
RANDERSON, JT ;
MALMSTROM, CM .
REMOTE SENSING OF ENVIRONMENT, 1995, 51 (01) :74-88
[10]   Estimation of spatial and temporal changes in net primary production based on Carnegie Ames Stanford Approach (CASA) model in semi-arid rangelands of Semirom County, Iran [J].
Hadian, Fatemeh ;
Jafari, Reza ;
Bashari, Hossein ;
Tartesh, Mostafa ;
Clarke, Kenneth D. .
JOURNAL OF ARID LAND, 2019, 11 (04) :477-494