Littérature scientifique sur le sujet « Digital repeat imagery phenology »

Researchers interested in remote locations have developed monitoring schemes, sometimes called “Watchful Eye” monitoring, that use a time series of remotely sensed images to assess changes over time to a protected area or habitat. For instance, the European Space Agency (ESA) and UNESCO have set up repeat analyses of satellite imagery for World Heritage sites. The first area for which they developed this technique was the habitat of the critically endangered mountain gorilla (Gorilla berengei berengei) in the Virunga Mountains in Central Africa, including the Bwindi and Mgahinga National Parks in Uganda, the Virunga and Kahuzi-Biega National Parks in the Democratic Republic of Congo, and the trans-boundary Volcanoes Conservation Area. The project developed detailed maps of these inaccessible zones so that protected area managers can monitor the gorilla habitat. Previously, available maps were old and inaccurate (at times handmade), did not completely cover the range of the gorillas, and did not cross national boundaries. Because there was no systematic information from the ground regarding changes over time, researchers also used remotely sensed data to complete change detection analyses over the past two decades. Using both optical (Landsat series) and radar (ENVISAT ASAR) satellite data, researchers were able to quantify rates of deforestation between 1990 and 2003 and relate these rates to human migration rates into the area resulting from regional political instability. Researchers constructed the first digital base maps of the areas, digital elevation models (DEMs), and updated vegetation and land use maps. They faced significant problems in both field and laboratory activities, including lack of existing ground data, dense vegetation cover, and fairly continuous cloud cover. They therefore used a combination of ESA ENVISAT ASAR as well as Landsat and ESA Medium Resolution Imaging Spectrometer (MERIS) optical data. The radar images allowed them to quantify elevation and distances between trees and homes. Landsat and MERIS data helped identify forest cover types, with Landsat providing finer-scale images at less frequent intervals and MERIS serving lower-resolution images more frequently.

Biomass is monitored in many agricultural studies because it is closely related to the growth of the crop. The technique of digital repeat photography that continuously capture images of a given area with an RGB or near-infrared enabled cameras, Phenocams, has been used for more than a decade mainly to estimate phenology. Studies have found a relationship between Phenocam data and above-ground dry biomass. In this context we investigate the modeling of barley fresh above and underground biomass with Green chromatic coordinate (Gcc) colour index, extracted from Phenocam data, and multi-output G

Abstract A set of Heavy Vacuum Gas Oil (HVGO) pumps in a 300 kbbl/day operating Upgrader Plant experienced repeated failures; typically less than 7 weeks. The pumps run continuously in a high-pressure, high temperature and corrosive environment and their functional status directly affects the reliability of the plant. Upon research, an experimental strain measurement technique using very high resolution laser digital imagery and optical metrology was found from military and advanced aerospace applications to verify high level dimensional accuracy of critical components [1]. Application to a co