Difference between revisions of "Productivity Maps"

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=== Learn the basics  ===
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Please review the following articles, to get familiar with the basics on Remote Sensing for Agriculture:
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*'''[http://www.extension.org/pages/Agricultural_Remote_Sensing_Basics Remote Sensing Basics]''' (extension.org)
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*'''[http://extension.missouri.edu/publications/DisplayPub.aspx?P=EQ453 Precision Agriculture: Remote Sensing and Ground Truthing]''' (University of Missoury Extension)
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*'''[[NDVI - Vegetation Index|Normalized Differential Vegetation Index (NDVI) Maps]]'''
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=== Overview  ===
 
=== Overview  ===
  
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[[Category:Farm_services]] [[Category:Productivity_maps]]
[[Category:Productivity_maps]]
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Revision as of 08:40, 6 December 2010

Learn the basics

Please review the following articles, to get familiar with the basics on Remote Sensing for Agriculture:




Overview

Productivity Zones maps are generated based on the combination of Vegetation Index maps, through a process called 'cluster analysis'. It's also possible to include information from previous yield monitor maps if available. 

This is a procedure relatively simple, automated and objective, that allows to compare the field production and variability in different times, in a single map. Remote sensing imagery is selected in key dates, when crops are vigorous, and Vegetation Index (NDVI) maps are generated on those dates. These layers are then normalized, and integrated in the productivity zone map.


Methodology - Cluster analysis

A cluster is a predefined area, for statistical analysis purposes. For instance a cluster could be the pixel of a satellite image, such as 30x30 mts for Landsat images, 15 x 15 mts for Aster images, or 10 x 10 mts for Spot images. Once the Cluster area is defined, a normalized NDVI map is generated, with a grid with the cluster size.

the following sample images and corresponding NDVI illustrate the process:


Landsat TM5 8mar04

NDVI 8mar04

Landsat TM5 6jan05

NDVI 6jan05

Landsat TM5 25jan06
NDVI 25jan06


These images are integrated by analyzing each cluster, defining homogeneous production areas, and obtaining the productivity zones map.
Management Zone Map













Limitations

Processing is carried out at the field level. The main reason is that in a given farm, fields may have at the same time different types of crops or uses. Thus, NDVIs from different fields cannot be compared. For this reason different images are selected for different fields.

As a conclusion, productivity zones maps should only be used to compare variability within fields, but not as a means of comparison between different fields.

Applications and Benefits

Productivity zones maps provide guidance to know the variability within a given field. Based on this knowledge, field visits can be carried out, making decisions regarding field management, management zone delineation, selecting areas for tests, etc.

Using productivity zones to define sampling points makes possible to review on site the different zones and the reasons behind the possible limitations.

This can be a starting point to delineating management zones, define inputs and recommendations, and selecting the type and quantity of inputs according to the management zones.