L. A. S. Romani, R. R. V. Goncalves, J. R. Zullo, J. R. Traina and A. J. M. Traina, “New DTW-Based Method to Similarity Search in Sugar Cane Regions Represented by Climate and Remote Sensing Time Series,” International Geoscience and Remote Sensing Symposium, Hawaii, 25-30 July 2010, pp. 355-358.

has been cited by the following article:

• TITLE: Trend Analysis of Small Scale Commercial Sugarcane Production in Post Resettlement Areas of Mkwasine Zimbabwe, Using Hyper-Temporal Satellite Imagery

  AUTHORS: Shingirirai Mutanga, Abel Ramoelo, Tichatonga Gonah

  KEYWORDS: Trend Analysis; Spot Vegetation; NDVI and Sugarcane

  JOURNAL NAME: Advances in Remote Sensing, Vol.2 No.1, March 25, 2013

  ABSTRACT: This study used normalized difference vegetation index (NDVI) derived from Spot Vegetation images as a proxy for sugarcane growth and production model. Time series analysis was undertaken using the moving average computed in R Programming language to monitor sugarcane production after the inception of land reform in the Mkwasine Estate of Zimbabwe. Overall the findings showed a declining trend with a few years of improved production over the 11 year period under investigation. To attest the possible explanations for the observed trend the study related NDVI data with climate variables and considered non climate factors such as land tenure. The predicted yield estimates over the years correlated very well with rainfall. The study therefore envisaged that hyper-temporal satellite imagery can be used to monitor sugarcane production and enhance decision making for future policy direction.