Assessment of Wheat Straw Cover and Yield Performance in a Rice-Wheat Cropping System by Using Landsat Satellite Data

Muhammad Sohail Memon, Zhou Jun, Chuanliang Sun, Chunxia Jiang, Weiyue Xu, Qiong Hu, Hangxu Yang and Changying Ji
Additional contact information
Muhammad Sohail Memon: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Zhou Jun: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Chuanliang Sun: Institute of Agricultural Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
Chunxia Jiang: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Weiyue Xu: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Qiong Hu: Key Laboratory for Geographical Process Analysis & Simulation Hubei Province/School of Urban and Environment Sciences, Central China Normal University, Wuhan 430079, China
Hangxu Yang: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China
Changying Ji: College of Engineering, Nanjing Agricultural University, Nanjing 210031, China

Sustainability, 2019, vol. 11, issue 19, 1-21

Abstract: Proper straw cover information is one of the most important inputs for agroecosystem and environmental modeling, but the availability of accurate information remains limited. However, several remote-sensing (RS)-based studies have provided a residue cover estimation and provided spatial distribution mapping of paddy rice areas in a constant field condition. Despite this, the performance of rice crops with straw applications has received little attention. Furthermore, there are no methods currently available to quantify the wheat straw cover (WSC) percentage and its effect on rice crops in the rice-wheat cropping region on a large scale and a continuous basis. The novel approach proposed in this study demonstrates that the Landsat satellite data and seven RS-based indices, e.g., (i) normalized difference vegetation index (NDVI), (ii) Normalized difference senescent vegetation index (NDSVI), (iii) Normalized difference index 5 (NDI5), (iv) Normalized difference index 7 (NDI7), (v) Simple tillage index (STI), (vi) Normalized difference tillage index (NDTI), and (vii) Shortwave red normalized difference index (SRNDI), can be used to estimate the WSC percentage and determine the performance of rice crops over the study area in Changshu county, China. The regression model shows that the NDTI index performed better in differentiating the WSC at sampling points with a coefficient of determination ( R 2 = 0.80) and root mean squared difference (RMSD = 8.46%) compared to that of other indices, whereas the overall accuracy for mapping WSC was observed to be 84.61% and the kappa coefficient was κ = 0.76. Moreover, the rice yield model was established by correlating between the peak NDVI values and rice grain yield collected from ground census data, with R 2 = 0.85. The finding also revealed that the highest estimated yield (8439.67 kg/ha) was recorded with 68% WCS in the study region. This study confirmed that the NDVI and NDTI algorithms are very effective and robust indicators. Also, it can be strongly concluded that multispectral Landsat satellite imagery is capable of measuring the WSC percentage and successively determines the impact of different WSC percentages on rice crop yield within fields or across large regions through remote sensing (RS) and geographical information system (GIS) techniques for the long-term planning of agriculture sustainability in rice-wheat cropping systems.

Keywords: agricultural sustainability; remote sensing; Landsat; crop yield; GIS; spatial analysis; wheat straw cover percentage; vegetation indices (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/19/5369/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/19/5369/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:19:p:5369-:d:271691

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().