|
|
Friends of the Environment
The
GLOBE Team at the Amman Baccalaureate School has been cooperating with friends
of environment society, Amman- Jordan for the past five years. This cooperation
has resulted in many students learning much about the use of remotely sensed
data for land cover mapping as well as the required protocols for collecting
ground sample site information. Our team has used advanced image classification
techniques to produce a land cover map of North West Amman region, from Landsat
Thematic Mapper imagery. The classification scheme used to make this map was
the Modified UNESCO Classification (MUC) scheme. Amman baccalaureate school has
conducted numerous daylong ground data collection campaigns, called
MUC-A-THONS. These ground-collected land cover sample sites provide an
excellent source of data for us.
In our land cover mapping project. The student-collected MUC-A-THON data were
used in conjunction with additional ground data collected by our Team to create
the map.
We are now making further studies comparing the image of 1997 and that of
2002 as a proceeding step to this project to monitor the environmental
changes.
Introduction:
Globally, there is a lack of accurate land cover maps available for use
in environmental management that includes monitoring deforestation,
biodiversity, water quality, ecosystem health, and urban sprawl. Important
decisions are based on these maps.
Students participating in the Global Learning and Observations to Benefit the
Environment (GLOBE) Program have the opportunity to provide large quantities of
accurate reference data necessary to validate and assess the accuracy of land
cover maps representing many areas of the world. (1)
An important question that arose early in the development of the program was,
if students from countries around the world could collect environmental data,
would that data be useful to scientists? In order to provide reliable data that
would be trusted by the scientific community, GLOBE incorporated measurements
and protocols developed by scientist/educator teams led by a Scientist
Principal Investigator and Educator Co-Principal Investigator (Finarelli,
1998). These protocols offer a consistent method of data collection, and if
properly followed, will produce accurate data which can be entered into the
GLOBE database and used by the scientific community worldwide (Rock and
Lawless, 1997).
Hence, the objectives of this study were:
? To generate a land cover map from remotely sensed data,
The objective of our
next studies is to:
? To test the overall accuracy of student-collected data
? To use the student-collected reference data to validate the land cover map
Literature Review
In this project, the land cover is classified using The Modified UNESCO
Classification (MUC) system (UNESCO, 1973). The new system incorporated new
land cover types absent from many other classification systems. MUC contains
all the characteristics of a good classification system, and allows for every
possible land cover type on Earth to be put into a unique land cover class.
Each MUC class is a distinct type of land cover, with a name and identification
number, or MUC class "code". By using MUC, all the GLOBE data may be compiled
into a single regional or global land cover data set. Therefore, ground
collected data may be gathered and used to validate remotely sensed data
following the same scientific protocols worldwide. There are ten Level 1
classes (Table 1). Classes 0-7 are natural land cover and classes 8-9 are
developed. These ten classes can be further broken down into four levels of
classification with each level increasing in detail (GLOBE, 1997).
Level 1 Category
0 Closed Forest
1 Woodland
2 Shrubland
3 Dwarf-shrubland
4 Herbaceous Vegetation
5 Barren Land
6 Wetland
7 Open Water
8 Cultivated Land
9 Urban
Friends of
the Environment
Amman - Jordan
|
|