LAB GUIDE

For purposes of applying the system for image classification, we must differentiate the information classes represented by the land use/land cover classification system from the spectral classes that we can obtain from the imagery. Often an information class will have a range of spectral responses that represent the inherent variability within a class that is intended to capture like activities. This may be due to composition of covers that are necessary to express the class, e.g., residential class would include materials for roads, lawns/gardens, rooftops and other building materials. Or, multiple land covers may individually satisfy the criteria for a given land use class, e.g., crops of barley, corn, lettuce, sugar beets, etc are all in the class “field crop”, but would have different spectral responses. The diurnal and seasonal aspect also contributes to spectral variability due to variation in planting dates, vegetation phenology, and illumination. Thus multiple spectral classes, called signatures or training sites, that capture the variability are required to represent a single information class.

Description of Study Area

In this module, we work through techniques to classify a portion of the North Coast of Honduras using Enhanced Thematic Mapper imagery for March 2003. The classification scheme is one used by Forestry Department in Honduras and is based on the FAO Land Cover classification system. For purposes of this exercise, we are working with 30m spatial resolution data and that is consistent with Level II of the system and in some cases Level III. The image processing routines described are based on Leica Geosystems ERDAS Imagine software.

See remainder of tutorial in the PDF document attached. Below are other resources from a workshop held in Honduras (April 2006) that will give you further introduction to LULC.

• FRA2000 - DEFINITIONS OF FOREST AND RELATED LAND USE CLASSIFICATIONS AND FOREST CHANGE PROCESSES
• FRA 2000 - Global Mapping document
• FRA 2000 Main Report
• FAO - Forestry Home page
• FAO - Honduras Forestry page
• GLCN - home page
• GLCN/LCCS Concept and its application in Africa as the AFRICOVER Project.
• GLCN Workshop in Costa Rica
• GLCN - Descriptive document

Here is a basic Map/Graphic checklist to help you assess the final output of your lab work which in most cases will be a map or series of maps. You may also be asked to produce a portfolio or poster with additional explanatory or content information--see criteria/rubric for policy-briefs or papers...

Key Map Elements included: Title,
Scale (graphic and Ratio), Legend,
Compass Rose or North Arrow).....................1     2     3     4     5

Uses appropriate projections and datums.......1     2     3     4     5

Grammar, spelling, fonts, lettering
(appropriate for users and audience).............1     2     3     4     5

Visual appeal (color/line quality)....................1     2     3     4     5

Accuracy/types of spatial data and
analytic methods fully documented.................1     2     3     4     5

Conciseness and focus (not too busy).............1     2     3     4     5

Relevance to user needs and audience............1     2     3     4     5

Persuasiveness of map--to the point...............1     2     3     4     5

Timeliness of content and data........................1     2     3     4     5

Quality and diversity of sources cited
(all sources cited appropriately)......................1     2     3     4     5


               TOTAL POINTS POSSIBLE   =     50

Points Earned X 2   =    ___ (Total out of 100 points)

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Bob Ford Home	Earth System Science Core Courses - LLU-SST - EBS
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