Difference between revisions of "How are productivity maps generated?"

From Wikiagro.com
Jump to: navigation, search
(Created page with "How are they generated understand the zones/ evaluate field variability – NDVI/ when to take imagery by crop? ...El Indice de Vegetación de Diferencias Normalizadas (NDVI por ...")
 
Line 3: Line 3:
 
...El Indice de Vegetación de Diferencias Normalizadas (NDVI por sus siglas en ingles) constituye una buena medida de la actividad fisiológica de las plantas, y además en estudios empíricos tiene entre un 85 y 90% de correlación con el rendimiento del cultivo.  
 
...El Indice de Vegetación de Diferencias Normalizadas (NDVI por sus siglas en ingles) constituye una buena medida de la actividad fisiológica de las plantas, y además en estudios empíricos tiene entre un 85 y 90% de correlación con el rendimiento del cultivo.  
  
Productivity maps are generated based on the combination of Vegetation Index maps, through geo-statistical analysis. It's also possible to include information from previous yield monitor maps if available.
+
=== Learn the basics  ===
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 map.
+
the following sample images and corresponding NDVI illustrate this 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 map.
+
  
Productivity Map
+
Please review the following articles, to get familiar with the basics on Remote Sensing for Agriculture:
 +
 +
*'''[http://www.extension.org/pages/Agricultural_Remote_Sensing_Basics Remote Sensing Basics]''' (extension.org)
 +
*'''[http://extension.missouri.edu/publications/DisplayPub.aspx?P=EQ453 Precision Agriculture: Remote Sensing and Ground Truthing]''' (University of Missoury Extension)
 +
*'''[[NDVI - Vegetation Index|Normalized Differential Vegetation Index (NDVI) Maps]]'''
 +
<br>
 +
 
 +
----
 +
 
 +
<br>
 +
 
 +
=== Overview  ===
 +
 
 +
Productivity maps are generated based on the combination of Vegetation Index maps, through geo-statistical analysis. It's also possible to include information from previous yield monitor maps if available.&nbsp;
 +
 
 +
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 map.
 +
 
 +
the following sample images and corresponding NDVI illustrate this process:
 +
 
 +
'''<br>'''
 +
 
 +
{| cellspacing="1" cellpadding="1" border="1" width="200"
 +
|-
 +
| [[Image:MZ landsat 8mar04.jpg|thumb|center|200px|Landsat TM5 8mar04]]<br>
 +
| [[Image:MZ NDVI 8mar04.jpg|thumb|center|200px|NDVI 8mar04]]<br>
 +
|-
 +
| [[Image:MZ landsat 6jan05.jpg|thumb|center|200px|Landsat TM5 6jan05]]<br>
 +
| [[Image:MZ NDVI 6jan05.jpg|thumb|center|200px|NDVI 6jan05]]<br>
 +
|-
 +
| [[Image:MZ landsat 25jan06.jpg|thumb|center|200px|Landsat TM5 25jan06]]
 +
| [[Image:MZ NDVI 25jan06.jpg|thumb|center|200px|NDVI 25jan06]]
 +
|}
 +
 
 +
<br>
 +
 
 +
These images are integrated by analyzing each cluster, defining homogeneous production areas, and obtaining the productivity map. [[Image:MZ management zone map.jpg|frame|left|500px|Management Zone Map]]
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
<br>
 +
 
 +
=== 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.<br>
 +
 
 +
<br>
 +
 
 +
 
 +
== Productivity Map ==
 
La definición de ambientes se inicia en una campaña determinada pero es un proceso que permite mejorar continuamente especialmente al finalizar la primer campaña con la obtención de mapas de rendimiento. A partir de ellos se puede obtenerse información valiosa para retroalimentar el mapa de ambientes original.
 
La definición de ambientes se inicia en una campaña determinada pero es un proceso que permite mejorar continuamente especialmente al finalizar la primer campaña con la obtención de mapas de rendimiento. A partir de ellos se puede obtenerse información valiosa para retroalimentar el mapa de ambientes original.
 +
 +
[[Category:Productivity_maps]]

Revision as of 07:46, 14 September 2012

How are they generated understand the zones/ evaluate field variability – NDVI/ when to take imagery by crop? ...El Indice de Vegetación de Diferencias Normalizadas (NDVI por sus siglas en ingles) constituye una buena medida de la actividad fisiológica de las plantas, y además en estudios empíricos tiene entre un 85 y 90% de correlación con el rendimiento del cultivo.

Learn the basics

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




Overview

Productivity maps are generated based on the combination of Vegetation Index maps, through geo-statistical 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 map.

the following sample images and corresponding NDVI illustrate this 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 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.



Productivity Map

La definición de ambientes se inicia en una campaña determinada pero es un proceso que permite mejorar continuamente especialmente al finalizar la primer campaña con la obtención de mapas de rendimiento. A partir de ellos se puede obtenerse información valiosa para retroalimentar el mapa de ambientes original.