Publication Date

12-2022

Series Number

428

Publisher

Department of Primary Industries and Regional Development

City

Perth

ISSN

1039-7205

Abstract

Maintaining vegetative groundcover is an important component of sustainable agricultural systems and plays a critical function for soil and land conservation in Western Australia’s (WA) grainbelt (the south-west cropping region). This report describes how satellite imagery can be used to quantitatively and objectively estimate total vegetative groundcover, both in near real time and historically across large areas. We used the Landsat seasonal fractional groundcover products developed by the Joint Remote Sensing Research Program from the extensive archive of Landsat imagery. These products provide an estimate of the percentage of green vegetation, non-green vegetation and bare soil for each 30 m pixel across WA on a seasonal basis and can be downloaded from TERN (Terrestrial Ecosystem Research Network) Data Discovery Portal.

The advantages the Landsat-derived fractional cover provides are:

  • non-arable land can be removed (masked) from the analysis because of the relatively high 30-m pixel resolution
  • the reported overall product accuracy is considered very good for remote sensing products (root mean square error of 11.6%)
  • the product is accessible and ready for immediate use
  • the large archive of past imagery dating back to 1987 is available for analysis of longer-term trends.

We processed the fractional cover data using a series of scripts (computer code written in Python programming language) to calculate the total vegetative groundcover for each pixel and determine the proportion of arable land in defined groundcover classes across the grainbelt or within areas of interest. This workflow delivers consistent outputs, including summary data tables and display graphics, answering the following questions:

  • What is the current groundcover status on arable land? Output: the percentage of land with ‘X’ groundcover.
  • Where is the highest erosion hazard? Output: a map of groundcover.
  • How does current groundcover compare to previous years? Output: options for maps, tables and graphs.

We use outputs from this remote sensing workflow to report on key performance indicator (KPI) for groundcover and annual soil erosion hazard for the Commissioner of Soil and Land Conservation. The analysed imagery also enables us to provide valuable regional farming systems intelligence to guide targeted extension messaging to assist landholders to prevent land degradation and ensure farming enterprises are productive and sustainable.

Number of Pages

42

Keywords

Landsat satellite imagery, estimating groundcover, erosion hazard, Python programming, grainbelt, Western Australia

Disciplines

Agriculture | Databases and Information Systems | Environmental Monitoring | Natural Resources and Conservation | Natural Resources Management and Policy | Programming Languages and Compilers | Soil Science | Sustainability

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