- freely available
Remote Sens. 2017, 9(1), 71; doi:10.3390/rs9010071
- Test our algorithm in a highly heterogeneous urban landscape to map the urban extent on a yearly basis;
- Quantify the patterns and trends of urban growth in NWA based on the generated urban extent maps.
2. Materials and Methods
2.1. Study Area
2.2. Image Acquisition and Preprocessing
2.3. Classification System and Classification Sample Selection
- Low-intensity urban: a less developed area where impervious surfaces account for 50% to 80% of the total cover, mostly containing residential areas such as neighborhoods, apartments, and roadways [36,37]. Dirt and gravel roads were not included in either of the urban classes due to their spectral signatures being similar to bare soils, harvested croplands, and water coastlines. To minimize confusion, only paved roads were included in the classification scheme;
- Agriculture/Pasture/Bare Lands: open areas of crops planted by farmers, grass, or other short vegetative growth in fields and bare patches of lands that lack intense vegetation. In NWA, due to Tyson Foods Inc., there are many pasture lands that are dedicated to the cultivation and harvest of poultry and beef. Agriculture in NWA is not as common as it is in the rest of Arkansas, but is present in the region. Bare lands are areas that have not been used for agriculture or pasture for animals, and are usually land stocks for urban expansion;
- Forest: an area that is dominated mostly by dense tree cover. NWA contains a number of national forests and parks, including the Ozark National Forest. These forested areas are, for the most part, very homogeneous in nature, containing about 80% to 100% tree cover with very little gaps. These gaps would be classified into the Agriculture/Pasture/Bare lands classification;
- Water: includes lakes, ponds, rivers, streams, and creeks that are visually identifiable on the Landsat imagery.
- More than 30 samples required for each class, which is the standard number of minimum samples necessary for accurate classification based on the sample size formula as recommended by .
- Samples needed to be greater than four pixels in size.
- Samples needed to be homogeneous in nature.
2.4. Classification Framework
2.4.1. Preliminary Classification
2.4.2. Anomaly Detection and Temporal Filtering
2.4.3. Urban Change Logic Rule
2.5. Accuracy Assessment
3.1. Accuracy Assessment
3.2. Urban Expansion in Northwestern Arkansas (NWA)
4.1. Pros and Cons of the Temporal Trajectory Polishing Algorithm
4.2. Socio-Economic and Environmental Explanations of the Urban Sprawling Patten in NWA
Conflicts of Interest
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