Difference between revisions of "Productivity Maps"

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(New page: == Management Zones == === Overview === Management Zones maps are generated based on the combination of Vegetation Index maps, through a process called 'cluster analysis'. It's also pos...)
 
 
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== Management Zones ==
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=== Learn the basics ===
  
=== Overview ===
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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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Management 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.&nbsp;
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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 maps are generated on those dates. These layers are then normalized, and integrated in the management zone map.
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=== Methodology - Cluster analysis ===
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=== Overview  ===
  
Se entiende por cluster a una unidad de superficie predeterminada, que sirve de base para un análisis estadístico. Se puede tomar como cluster, por ejemplo, el píxel de una imagen satelital, siendo para las Landsat 30 x30 mts, para las Aster 15 x 15 mts, para las Spot 10 x 10 mts.  
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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;
  
Una vez definida la superficie del Cluster, se generan mapas de NDVI normalizados (cuya grilla tenga el mismo tamaño que los píxeles de las imágenes satelitales). Las capas de NDVI son creadas a partir de imágenes seleccionadas de acuerdo a fechas claves, donde los cultivos reflejan vigorosidad.  
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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.  
  
<br>Este es un procedimiento que realizamos exclusivamente a nivel de lote.
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the following sample images and corresponding NDVI illustrate this process:
  
<br>En el siguiente ejemplo se muestras las imágenes utilizadas:
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'''<br>'''
  
<br>Image:IMAGEN_1.jpg Imagen Landsat 25-01-2006
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{| cellspacing="1" cellpadding="1" border="1" width="200"
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|-
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| [[Image:MZ landsat 8mar04.jpg|thumb|center|200px|Landsat TM5 8mar04]]<br>  
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| [[Image:MZ NDVI 8mar04.jpg|thumb|center|200px|NDVI 8mar04]]<br>
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|-
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| [[Image:MZ landsat 6jan05.jpg|thumb|center|200px|Landsat TM5 6jan05]]<br>
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| [[Image:MZ NDVI 6jan05.jpg|thumb|center|200px|NDVI 6jan05]]<br>
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|-
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| [[Image:MZ landsat 25jan06.jpg|thumb|center|200px|Landsat TM5 25jan06]]
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| [[Image:MZ NDVI 25jan06.jpg|thumb|center|200px|NDVI 25jan06]]
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|}
  
<br>Imagen Landsat 06-01-2005
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<br>Imagen Landsat 08-03-2004
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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]]
  
 
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A partir de las imagenes anteriores se realizan sus correspondientes indices verdes
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=== Limitations  ===
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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.
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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.
  
Image:NDVI_1.jpg NDVI Landsat 25-01-2006
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=== Applications and Benefits  ===
  
<br>NDVI Landsat 06-01-2005
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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.
  
<br>NDVI Landsat 08-03-2004
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Using productivity zones to define sampling points makes possible to review on site the different zones and the reasons behind the possible limitations.
  
<br>Al tener listas todas las capas de NDVI necesarias, se analizan por cluster, lo que permite definir zonas homogéneas y obtener como resultado un mapa de productividad.  
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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>
  
Image:Mapa_productividad3.jpg
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<br>Category:Servicios <br>
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[[Category:Productivity_maps]]

Latest revision as of 13:08, 25 January 2012

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.