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Airborne Laser Swath Mapping instrument technology and subsequent algorithm advances have made it possible over the last few years to map the Earth's surface and land cover at unprecedented resolution.
Recognition of geomorphic features, such as landslide scarps, is the first key step for landslide risk assessment and mitigation. Geomorphic features can be identified from high-resolution digital elevation model (DEM).
We analysed spectral and textural attributes from the Advanced Land Imager (ALI)/EO-1 for land-cover mapping and inspected their correlation with biophysical parameters of primary and secondary forests from Eastern Amazon.
The objective of this article is to develop and test a methodology capable of using medium spatial resolution satellite imagery to improve forest-area statistics derived from ground sampling.
Improved change vector analysis (ICVA) has recently been promoted as an effective algorithm for multi-class change detection. Unlike the conventional change vector analysis (CVA) that works on two-dimensional data, the ICVA works on multidimensional data.
This article introduces an innovative approach using marker-controlled watershed segmentation (WS) in the Vegetation–Impervious Surface–Soil (V–I–S) feature space for urban land-use and land-cover (LULC) classification.
A geoinformatics-based land suitability assessment approach was used to examine the prospects for precision farming in the Savanna River basin in Nigeria.
This paper presents an objective approach for quantifying the amount of mangrove loss caused by expansion of shrimp farms in three villages of Krabi Province, Thailand.
National Agriculture Imagery Program (NAIP) orthophotography is a potentially useful data source for land cover classification in the United States due to its nationwide and generally cloud-free coverage, low cost to the public, frequent update interval, and high spatial resolution.
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