1a. Can change detection be used to monitor events that take place over short time periods and long time periods?
1b. Is the study of land cover change over time important only at a local level or are there reasons to study land cover change on a global scale?
1c. Is it possible to use change detection methods to predict what changes will take place in the future? What are some examples of this?
2a. If the spatial resolution of a satellite image is 30m, could a change in cover type be detected between two different dates if the area of change was 30m by 30m?
2b. If a habitat or land cover type is described as highly fragmented, what does that mean?
2c. What is meant by temporal resolution?
3a. Are automated digital change detection techniques more reliable than manual interpretation techniques?
3b. What are some of the limitations or problems that can be encountered in change detection methodologies?
1a. Yes, as long as good data or imagery at the required time frequency are available. See Introduction and Section 1.
1b. Studying land cover change is important at a wide range of spatial scales. Some cases of land cover change may only significantly impact local or regional areas, however other land cover dynamics may manifest signals with relevance to global processes and the health of the biosphere, such as global warming, pollution, destruction of the ozone layer, habitat destruction, and soil depletion. See Section 1.1.
1c. Yes. It is possible to use change detection techniques in concert with predictive models to forecast the effects of environmental modifications. Some examples of this are predicting climate change, crop failures, and consequences of resource depletion.
2a. Probably not. As a rule of thumb, four pixels are needed to confirm identity, and ten pixels are needed to measure acreage. In this case an area of about 60m by 60m would have to change for it to be reliably detected by a sensor having 30m spatial resolution. The area would have to be much larger for its acreage to be measured accurately. However, detecting change also depends on the contrast in reflectance before and after the change. The greater the contrast, the smaller the area needed to detect the change. See Section 2.1.1.
2b. Fragmentation refers to the continuity of areas having a particular land cover type and environmental conditions. A highly fragmented area or habitat contains a patchwork of different cover types with no large contiguous parcels of a single land cover type remaining. See Section 2.1.2.
2c. Temporal resolution in remote sensing refers to the observation frequency of an area or event, that is, the number of observations per unit time. The optimum temporal resolution is usually determined by the expected rate of change of the vegetation or land cover. See Section 2.1.1.
3a. Not necessarily. Since the human eye is very good at distinguishing tones, textures, shapes, and spatial relationships, manual visual interpretation techniques performed by experienced analysts are quite reliable. However, automated digital change detection techniques save time and intensive labor, and may be helpful if cover change is subtle. See Section 3.
3b. The goal of change detection is to identify real, actual change. Factors limiting the accurate detection of actual change include inadequate spatial and temporal resolutions of the image data, spectral characterization/specification of key indicators of change, view and sun angle variations in the remote sensing datasets, atmospheric conditions and corrections, errors in geographic registration, variable surface conditions such as soil moisture differences, and vegetation phenologies. Careful consideration of these factors and accounting for their effects can improve the accuracy of the change detection results.