Next Article in Journal
Realistic Simulation for Body Area and Body-To-Body Networks
Previous Article in Journal
High Resolution Trichromatic Road Surface Scanning with a Line Scan Camera and Light Emitting Diode Lighting for Road-Kill Detection
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(4), 557; doi:10.3390/s16040557

Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series

1
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
Key Lab of Agri-information Service Technology, Ministry of Agriculture of China, Agricultural Information Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
3
College of architecture and urban planning, Chongqing Jiaotong University, Chongqing 400074, China
4
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Assefa M. Melesse
Received: 16 November 2015 / Revised: 9 March 2016 / Accepted: 17 March 2016 / Published: 19 April 2016
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [6213 KB, uploaded 19 April 2016]   |  

Abstract

Multiple cropping provides China with a very important system of intensive cultivation, and can effectively enhance the efficiency of farmland use while improving regional food production and security. A multiple cropping index (MCI), which represents the intensity of multiple cropping and reflects the effects of climate change on agricultural production and cropping systems, often serves as a useful parameter. Therefore, monitoring the dynamic changes in the MCI of farmland over a large area using remote sensing data is essential. For this purpose, nearly 30 years of MCIs related to dry land in the North China Plain (NCP) were efficiently extracted from remotely sensed leaf area index (LAI) data from the Global LAnd Surface Satellite (GLASS). Next, the characteristics of the spatial-temporal change in MCI were analyzed. First, 2162 typical arable sample sites were selected based on a gridded spatial sampling strategy, and then the LAI information was extracted from the samples. Second, the Savizky-Golay filter was used to smooth the LAI time-series data of the samples, and then the MCIs of the samples were obtained using a second-order difference algorithm. Finally, the geo-statistical Kriging method was employed to map the spatial distribution of the MCIs and to obtain a time-series dataset of the MCIs of dry land over the NCP. The results showed that all of the MCIs in the NCP showed an increasing trend over the entire study period and increased most rapidly from 1982 to 2002. Spatially, MCIs decreased from south to north; also, high MCIs were mainly concentrated in the relatively flat areas. In addition, the partial spatial changes of MCIs had clear geographical characteristics, with the largest change in Henan Province. View Full-Text
Keywords: GLASS LAI; NCP; multiple cropping index; spatial and temporal changes; remote sensing GLASS LAI; NCP; multiple cropping index; spatial and temporal changes; remote sensing
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zhao, Y.; Bai, L.; Feng, J.; Lin, X.; Wang, L.; Xu, L.; Ran, Q.; Wang, K. Spatial and Temporal Distribution of Multiple Cropping Indices in the North China Plain Using a Long Remote Sensing Data Time Series. Sensors 2016, 16, 557.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top