1a. Why are vegetation dynamics important?
1b. What is the utility of long-term baseline records of vegetation dynamics?
1c. When creating a vegetation classification scheme, what are the drawbacks to defining numerous categories dependent on very detailed information?
1d. Is field verification of generated classes an important step in mapping vegetation?
2a. What is a hierarchical classification scheme? What are the advantages of such a design?
2b. What is a potential vegetation map? What conditions are used to create such a map?
2c. Would you expect a potential vegetation map to remain constant over long periods of time?
3a. Are vegetation reflectance properties constant through time with respect to a satellite- borne sensor?
3b. What are vegetation indices?
3c. What is a basic difference between a supervised and an unsupervised classification?
3d. What is the goal of accuracy assessment?
1a. Vegetation dynamics can be indicators of processes, productivity trends, and ecosystem interactions that can be otherwise difficult to monitor. See Section 1.
1b. Long-term records of vegetation dynamics help to establish the normal variability of various vegetation types. See Section 1.
1c. Defining too many detailed classes can lead to inaccuracy in classification, difficulties in implementation and mapping, and inapplicability in areas other than where the classes were originally defined. See Section 2.
1d. Yes. Field verification is necessary to validate results and check the accuracy of a classification. See Section 2.
2a. In a hierarchical approach, classes are nested such that major classes are broken into subclasses, and subclasses can be further broken into more sub-classes. The advantage of such a system is that it can be easily generalized and it is easy to adopt to various spatial scales. See Section 2.2.
2b. A potential vegetation map is a map of vegetation that could potentially exist under idealized conditions in a given area. Potential vegetation distribution is largely determined by climate and soils. See Section 2.3.
2c. No. Potential vegetation is hypothetical and, because it is largely determined by climate, it is not constant. For example, a potential vegetation map of the world at the time of the last ice age would differ from a vegetation map derived for current climatic conditions. See Section 2.3.
3a. No. They vary with the position of the solar light source (time of day and time of year, termed illumination angle) and with the position of the sensor relative to the imaged area (view angle). See Section 3.1.1.
3b. Vegetation indices condense the values from two (or more) spectral bands into a single parameter that is optimized for detecting vegetation. See Section 3.1.2.
3c. A basic difference between supervised and unsupervised classification is that supervised classification selects and characterizes representative cover types before running the classification, while unsupervised classification does not define specific classes beforehand. See Section 3.2.
3d. The goal of accuracy assessment is to determine how accurately and completely a classified image represents actual conditions and land cover.