From the analysis carried out in the GIS, the land use dynamics within the lease could be quantified and modelled. Temperature statistics for the region in 2000 33 List of red data species occurring in Zulti South 40 Hierarchical land cover and land use classification scheme.
INTRODUCTION
INTRODUCTION
This research focuses on the spatial approach in monitoring land use and land cover changes. Land use monitoring provides a means by which effective management of this dynamic resource can be achieved in an efficient and sustainable manner.
LAND USE
Similarly, in South Africa, land use monitoring is not a new phenomenon (Rivers-Moore, 1997; Read, 2001), but there are still relatively few examples or studies of land use monitoring. RBM requires more detailed monitoring of land use changes in order to manage and proactively react to these changes.
AIMS AND OBJECTIVES OF THE STUDY
To develop a land use classification, remote sensing and GIS framework for assessing and predicting land use change. It is beyond the scope of this study to provide a full analysis of the effects of land use changes on the ecological, social or economic environment of the study area.
LITERATURE REVIEW
LAND USE
- Land use change
Land use is defined as a specific combination of land activity and land cover. The usefulness of land use data depends on how accurate and representative the data is.
REMOTE SENSING
Land use interpretation can be facilitated by the fact that the interpreter has a holistic view of the study area. Orthophotos are corrected vertical aerial photographs that have removed most of the parallax in the original photograph, thus increasing the relevance of aerial photographs.
GIS AND LAND USE
- GIS and remote sensing
- Temporal GIS
- Change and Time series analysis
Spatial relationships of the data can be summarized, analytically processed within GIS, used to extract information inherent in the remotely sensed data to produce a strategic picture of land use (Bibby and Shepherd 1999, Goodchild 1993). Time series analysis concerns the study of changes in land use over a sequence of remotely sensed images (Eastman 1995, Langran 1991).
SUMMARY
STUDY AREA
- INTRODUCTION
- LOCATION OF THE STUDY AREA
- BID-PHYSICAL ENVIRONMENT
- Topography
- Vegetation
- Animallife
- CURRENT INFRASTRUCTURE AND LAND USE
- Formal land use and infrastructure
- Subsistence land use and infrastructure
- SUMMARY
The natural vegetation was mainly located in the southern, coastal and northern part of the lease area. Dune forest and pioneer species occur on the seaward slopes of the dune cordon.
MATERIALS AND METHODS
INTRODUCTION
To determine how and ,.re land use had changed in the study area over the time period, . a) calculated the area of land occupied by each land use category for each data set, .. b) modeled a time series comparison between land use maps, c) difference in occupied area for each class among different ones. In predicting possible future land use scenarios in the south of Zult. a) the direction of spatial and temporal land use change was identified, b) hotspots of potential change were identified, .. c) trends and patterns observed from land use maps were used to predict future scenarios of land use.
MAPPING LAND USE
LAND USE CLASSIFICATION
Taking into account the soil classification criteria discussed above, the land use and land cover classes highlighted in table 4.1 below were selected and used. Natural - this category includes all land that is covered by at least 60% natural vegetation indigenous to the study area. Cultivation - While this class can be used to cover a wide range of farming practices, it is included here to account for land held under subsistence farming leases.
All land under cultivation, recently harvested or planted, is included in this class. Formal - this category incorporates all legal commercial land use or services within the lease area. Disturbed – in general, this category includes all areas where significant vegetation cover of more than 40% has been removed, land lying fallow, bare land, land transitioning to another class, land that has been slashed and burned or land that is a exotic vegetation cover of more than 40% (which does not fall into the plantation or cultivation class).
PHOTO-INTERPRETATION
As Lo says, photo interpretation involves "deductive and inductive evaluation of the various elements detected in the photo in terms of common sense and field experience, supported by the interpreter's academic and practical background. This was done to reduce the amount of human error and to provide a high level of consistency when interpreting the remotely sensed images.
DATA COLLECTION
DATA CONSTRAINTS
As previously mentioned, photo interpretation is essentially subjective and relies on the human decision of the interpreter. This included a deductive and inductive evaluation of the seasonal differences detected in the photograph in terms of common sense and practical experience, supported by the academic and practical background of the interpreter of the study area.
RECTIFYING THE REMOTELY SENSED DATA
- Geo-referencing
- Mosaicing
The georectification was achieved using ER Mapper 6.0 software (see Figure 4.2 for a detailed breakdown of the methodology and process followed to rectify the raster images). Raster images by definition must be a regular grid, ER Mapper calculates the extent of the rectified images and fills the gaps in the data to create the rectangular image (Cuthbert pers. Com, 2001). The first row shows the x-scale of the image and is in the dimension of one pixel in map units in the x-direction.
The fourth line shows the y-scale of the image and is in one-pixel dimension in map units in the y-direction. To mosaic corrected orthophotos, the name and location of the first image must be entered into the Mozaicing Wizard (see figure 4.5), then the file types and additional images to be mosaicked to this image are selected. The Mosaicing wizard within ER Mapper will then combine these images to produce a single image of the entire study area.
CREATING LAND USE MAPS
- Editing and creating polygons
The final polygon coverage is then converted to a figure file containing polygons depicting the land use topology of the study area. This is done through a supervised classification procedure using the land use classes previously defined in the research (see section 3.3.2.). Each data set represents the spatial land use patterns present at the time the aerial photographs were taken for each of the orthophotos between September 1990 and June 2001.
Assessing the accuracy of the final land use maps is essential in identifying and correcting sources of error. Potential error can occur from the data acquisition stage where the wrong boundaries are digitized, or the classification stage where mapped regions are incorrectly classified or represented on land use maps. In this research, 50 random points of ground observations of land use were calculated against that mapped from the June 1, 2001 orthophotos.
DETECTING AND ANALYSING CHANGE
Observations were impossible and insufficient to develop error matr!x for other datasets due to land use conditions changing rapidly since the time the aerial photographs were taken, but visual comparison seemed to generally confirm the validity of the maps land use. By running the summary function and determining the total area for land use, the total area of each land use class was determined (results in chapters). To compare how land use has changed over a period of time, a time-series pairwise image discrimination technique was used.
For the purposes of the research, the base year was assumed to have no change in land use. Each data set was compared to the previous image to determine and quantify how land use has changed from one theme to the next. To achieve this, each individual land use theme was transformed into a grid with.
PREDICTING
SUMMARY
RESULTS
- LAND USE
- Accuracy Assessment
- Community land use
- LAND USE CHANGE
- Total change
- PREDICTION
- Community prediction
- SUMMARY
These two land use classes are mostly found within the dune cordon of the lease area. Other important land use contributions in dataset 1 are: degraded land accounting for 5.9% and cultivation 2.4% of the leased area. The total area occupied by each class of tribal land use is shown as a percentage of the total lease area (table 5.3).
The largest contribution to changes (Table 5.4) is that the plantation land use class is changed to disturbed 45.3 ha (1.5%). The majority of the land use change from dataset 1 to dataset 3 is in the form of plantation change to disturbed land on a total area of 135.2 ha (4.3%) in the lease area (Table 5.5). The majority of the change that occurs is plantation change to the disturbed land use class, which contributes to the tenancy.
The disturbed land use type occupies most of the tribal region with an area of 477 ha (15.5% of Zulti South) in January 2002. The natural land use type represents most of the tribal region with an area of 915.1 ha. ha (29.8% of Zulti South) in January 2002.
DISCUSSION
- LAND USE IN ZULTI SOUTH
- Land use
- LAND USE CHANGE
- Change from the base year
- PREDICTION
- Land Use Prediction
- Community Prediction
- Land use change prediction
- LIMITATIONS OF THE RESEARCH
- SUMMARY
Natural land use accounts for the highest area in each of the six data sets. However, there is a slight decrease in the utilized area for this data set of land use type 2 and 3. The difference in the type, area and location of land use change will be described and discussed.
The results (Table 5.4) show that the land use change between the datasets in Zulti South is sporadic with varying changes in the land use occurring. The total area of land use change occurring from the base data set increases throughout the time series. The results obtained from the land use forecasts (Table 5.8) for January and June 2002 were good.
CONCLUSION
- LAND USE
- LAND USE CHANGE
- LAND USE PREDICTION
- REFLECTIONS
- RECOMMENDATIONS
- CONCLUSION
Therefore, a standard a priori land use classification system was created that would be suitable for achieving the objectives in the project. In relation to changes in land use area over time series, certain patterns of land use change become apparent through GIS analysis. This suggests that the change in land use is as a result of the entry of tribal members into South Zulti along accessible roads.
Hot spots where land use change is likely to occur are shown to be land along roads, recently disturbed land or plantations adjacent to roads and disturbed lands. It would be valuable to assess the accuracy of the land use predictions made in this research. In conclusion, this research has shown the ability of a GIS system to contribute to the spatial phenomenon of land use monitoring.
Biodiversity and land use history of the Palouse bioregion: Pre-European to present.. http://biology.usgs.gov/luhna/chap10.html. Available: http://www.geog.utoronto.ca/gozdyra/teach/. Lectures_GGR272/8_Types_oCMaps_Choropleth_Map.htm. http://www.ncgia.ucsb.edu/education/curricula/cctp/units/unit14/14.html. Corporate Land Use Classification System for British Columbia: Justification and Specification.. http://WNW.for.gov.bc.calriclPubs/LandUselindex.htm.
An environmental assessment on the effects of surface mining in the KingsalTojan lease region of the eastern shores of Lake ST Lucia. Using a geographic information system to examine changes in land use patterns in the Midmar watershed. The Potential of GIS for Local Land Use Planning, a Case Study in Mae Chaem, Northern Thailand.
Land Use Classification
421 White pine forests 422 Hemlock forests 423 Spruce and fir forests 424 Longleaf pine forests 425 Scots pine forests 426 Second yellow pine forests 427 Pond pine forests.
ER Mapper Support
Land use trends
- Plantation I
- Homestead I
Tribal land use trends
