Crop Water Condition Mapping by Optical Remote Sensing

Road Condition Mapping with Hyperspectral Remote Sensing

1. Introduction The quality standards for transportation infrastructure have evolved considerably over the last three decades. The data accuracy requirements to support road management have decreased from tens of meters to a few decimeters with annual update rates. Roads are prioritized for maintenance and treatment as a result of pavement inspections. The cost of frequent, comprehensive inspec...

Water quality estimation by optical remote sensing in boreal lakes

Remote Sensing for Crop Management

Scientists with the Agricultural Research Service (ARS) and various government agencies and private institutions have provided a great deal of fundamental information relating spectral reflectance and thermal emittance properties of soils and crops to their agronomic and biophysical characteristics. This knowledge has facilitated the development and use of various remote sensing methods for non...

Uncertainty in ecosystem mapping by remote sensing

The classification of remotely sensed images such as aerial photographs or satellite sensor images for deriving ecosystem-related maps (e.g., land cover, land use, vegetation, soil) is generally based on clustering of spatial entities within a spectral space. In most cases, Boolean logic is applied in order to map landscape patterns. One major concern is that this implies an ability to divide t...

The Use of Optical Remote Sensing For Mapping Flooded Areas

Flood maps are a crucial tool to support emergency management, disaster recovery and risk reduction planning. Traditional flood mapping methods are time-consuming, labor intensive, and costly. Our goal in this paper is to introduce a novel technique to aggregate knowledge and information to map coastal flooded areas. We proposed a Difference of Normalized Difference Water Indices (DNDWI) derive...