The algorithm takes the red-to-green remote-sensing reflectance (Rrs band ratio of [Rrs 667) + Rrs 678)]/[Rrs 531) + Rrs 547)] as the independent variable, and estimates Chla through the non-linear regression function: Ln(Chla) = 1.91Ln(x) + 3.40 (R2 = 0.87, N = 97, p < 0.01, 1.5 < Chla < 80 mg m−3) where 'x' is the band ratio.
The PHENOTYPE project uses a range of novel tools and methods to assess access and use of green space including remote sensing, smartphones, audits and interviews.
Thus, our indicator accurately expresses the relationship between stakeholders' perceptions of ESS provided by green spaces and the physical data (i.e., green space structure) produced by remote sensing technology.
The green-up dates detected from remote sensing data typically occurred during crop vegetative stages when 2 4 leaves were developed for both corn and soybeans, or about 1 3 weeks after the reported emergence dates when the plant were first visible to ground-based observers.
We developed a spatially explicit indicator (or metric) called Normalized Difference Green-Building Volume (NDGB), derived from remote sensing, that can be used to predict the way people perceive the ESS conveyed by green spaces in cities.
In this study, we investigated the utility of hyperspectral remote sensing data for estimating green percent vegetation cover (PVC) for a study site in the Canadian High Arctic.
In a pilot study conducted in Kenya as part of a global assessment of land degradation and improvement, Bai and Dent (2006) also applied remote sensing successfully to quantify green biomass and net primary production.
In this paper, we investigated the relationship between the green chromatic coordinate (GCC) derived using near-surface remote sensing and a range of vegetation products derived from the Medium Resolution Imaging Spectrometer (MERIS) throughout the growing season.
The results of satellite remote sensing monitoring showed that this green tide covered approximately 3800 km2 [9].
Models for the estimation of the concentration of catechins concentration in new green tea shoots were established using ground-based hyperspectral remote sensing.
In this study, we used multispectral remote sensing images to extract urban buildings and green areas and developed a Building Visual Greenness Index (BVGI) to estimate the green space views from buildings.
