The ability to detect and quantify changes in the Earth’s environment depends on satellites sensors that can provide calibrated, consistent measurements of Earth’s surface features through time. A critical step in this process is to put image data from subsequent generations of sensors onto a common radiometric scale. To evaluate Landsat-5 (L5) Thematic Mapper’s (TM) utility in this role, image...

Landsat Enhanced Thematic Mapper Plus (ETM+) images were compared to Terra-MODIS imagery for detecting forest changes in northern Maine’s industrial forest. Advantages of MODIS imagery compared to medium spatial resolution imagery, like Landsat TM or ETM+, are its temporal frequency, its low data volume to cover large forest regions and, the data are free to download over the Internet. The obje...

This paper presents a Python QGIS (PyQGIS) plugin, which has been developed for the purpose of producing Land Surface Temperature (LST) maps from Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 TIRS, Thermal Infrared (TIR) imagery. The plugin has been developed purposely to ease the process of LST extraction from Landsat Visible, Near Infrared (VNIR) and TIR imagery. It has the ability to estimate L...

Vegetation health can be monitored using a time series of remotely sensed images by calculating the Normalized Difference Vegetation Index (NDVI). We assessed temporal trends throughout an NDVI time series with three sensors: Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/E...