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Published in Jeremiah Kipkulei Kiptala, Managing Basin Interdependencies in a Heterogeneous, Highly Utilized and Data Scarce River Basin in Semi-Arid Africa, 2020
The Moderate-resolution Imaging Spectroradiometer (MODIS) is an extensive program using sensors on two satellites (Terra and Aqua) to provide a comprehensive series of global observations of the Earth’s land, oceans, and atmosphere in the visible and infrared regions of the spectrum. Terra earth observation system (EOS) was launched in 1999 while Aqua EOS was launched in 2002. The time of overpass of Terra (EOS AM) satellite is 10.30a.m while Aqua (EOS PM) satellite is 13.30pm local time. The MODIS data is available in different versions, and the latest version 5 (V005) available from 2008 from the USGS database has been validated (USGS, 2012). The images were retrieved from the Land Processes Distributed Active Archive Center (LPDAAC) of the National Aeronautics Space Administration (NASA) [https://reverb.echo.nasa.gov/reverb]. The MODIS images required for the SEBAL model include land surface temperature (LST)/emmissivity (EMM), surface reflectance (SF) and vegetation index (VI) (Table 4.2).
Remote Sensing and Modeling of Global Evapotranspiration
Published in Ni-Bin Chang, Yang Hong, Multiscale Hydrologic Remote Sensing, 2012
Qiaozhen Mu, Maosheng Zhao, Running Steven W.
Remotely sensed data, especially those from polar-orbiting satellites, provide us with temporally and spatially continuous information over vegetated surfaces and are useful for accurately parameterizing surface biophysical variables, such as albedo, biome type, and leaf area index (LAI) (Los et al. 2000). As a result, remote sensing data can greatly reduce the uncertainties in ET estimates. The Moderate Resolution Imaging Spectroradiometer (MODIS), onboard the NASA satellites Terra and Aqua, may be the most complex instrument built on a spacecraft for civilian research purposes (Guenther et al. 2002). The MODIS sensor provides higher quality data for monitoring terrestrial vegetation and other land processes than previous sensors such as the Advanced Very High Resolution Radiometer (AVHRR), not only because of its narrower spectral bands that enhance the information derived from vegetation (Justice et al. 2002), onboard calibration to guarantee the consistent time-series reflectance (Guenther et al. 2002), and orbit and altitude satellite maneuvers to ensure subpixel geolocation accuracy (Wolfe et al. 2002) but also because leading scientists are working as a team to improve the accuracy of the data from low-level reflectance data to derived high-level land data.
Monitoring Ecosystem Toxins in a Water Body for Sustainable Development of a Lake Watershed
Published in Ni-Bin Chang, Kaixu Bai, Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing, 2018
The surface reflectance curves for chlorophyll-a and phycocyanin in surface waters peak at 525 nm, 625 nm, 680 nm, and 720 nm (Figure 17.1a). MEdium Resolution Imaging Spectrometer (MERIS) was one of the main instruments on board the European Space Agency (ESA)'s ENVISAT platform, and could have the capability to detect phycocyanin. Bands 5 and 8 of MERIS help distinguish the phycocyanin and chlorophyll that offer a powerful opportunity to quantify the microcystin concentration (Chang et al., 2014). Additional resources include the Moderate Resolution Imaging Spectroradiometer (MODIS), which is a payload scientific instrument that was launched into Earth orbit by NASA in 1999 on board the Terra (EOS AM) Satellite and in 2002 on board the Aqua (EOS PM) satellite as a paired operation. Vincent et al. (2004) used Landsat TM images in the visible and infrared spectral bands to predict phycocyanin concentrations with prediction accuracies from 73.8% to 77.4%. Shi et al. (2015) adopted a regression model that was validated and then applied to an 11-year series of MODIS-Aqua data to investigate the spatial and temporal distributions of microcystin levels in Lake Taihu, China. They concluded that, in addition to the existing spectral information, cyanobacterial bloom scums, temperature, wind, and light conditions could probably affect the temporal and spatial distribution of microcystin levels in Lake Taihu. Thus, the surface reflectance of phycocyanin, chlorophyll-a, and Microcystis are suitable indicators for the prediction of microcystin levels in a water body. However, in Figure 17.1a, the defining peaks and troughs for Landsat are smoothed out as the total reflectance is averaged for the bands. For this reason, due to the lack of such information associated with band 681 nm, the resulting Landsat band is most likely unable to detect embedded reflectance information essential for discerning some water quality constituents sensitive to optical properties and characterizing the species within a phytoplankton bloom (Chang et al., 2014). However, hyperspectral sensors like MERIS have more bands with much thinner bandwidths. These hyperspectral bands with more narrow bandwidths may accurately depict the spectral reflectance curve of the target constituents in a water body, as evidenced by Figure 17.1b. Hyperspectral information has two advantages due to the ability to introduce key hyperspectral information to include more degrees of freedom in species identification. One advantage is that it allows for optical models of higher explanatory power to quantify the nonlinear relationships between surface reflectance and water quality constituents, and the other is that it enhances the determination of inherent optical properties that vary with water depth for water column surveillance (Chang et al., 2004; Torrecilla et al., 2009).
Spatial and temporal variation of daytime and nighttime MODIS land surface temperature across Nepal
Published in Atmospheric and Oceanic Science Letters, 2019
Nirajan LUINTEL, Weiqiang MA, Yaoming MA, Binbin WANG, Sunil SUBBA
Land surface temperature (LST) is an indicative factor for climatic and environmental changes, and has been extensively used in the assessment of environmental features such as urban heat islands (Peng et al. 2018), vegetation conditions (Li et al. 2016), land-use and land-cover changes (Muro et al. 2018), drought severities (Karnieli et al. 2010), and climate changes (Eleftheriou et al. 2018; Khorchani et al. 2018), among others. The recent advancements in remote sensing have made the acquisition of LST data at high spatial and temporal resolutions feasible. Satellite-borne thermal sensors can efficiently record LST signals and have shown promising prospects for global monitoring by leveraging the acquisition of temperature data even from topographically complex regions where maintenance of observation stations is challenging. Among them, the Moderate Resolution Imaging Spectroradiometer (MODIS) is the most widely used, due to its high spatial and temporal resolution (1 km and 4 times a day), global coverage, and long-term dataset.
A new approach to LST modeling and normalization under clear-sky conditions based on a local optimization strategy
Published in International Journal of Digital Earth, 2022
Majid Kiavarz, Mohammad Karimi Firozjaei, Seyed Kazem Alavipanah, Quazi K. Hassan, Yoann Malbéteau, Si-Bo Duan
The Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric water-vapor product (MOD07 with a resolution of 5000 meters) is an estimate of the total tropospheric column water vapor made of integrated MODIS infrared retrievals of atmospheric moisture profiles in clear scenes. This product was used to complete the input variables of LST obtained from satellite imagery. Moreover, GDEM produced by Japan and the United States National Aeronautics and Space Administration (NASA) was used for modeling the NSTLR effect and the solar irradiance with absolute horizontal and vertical accuracies of 30 and 17 m. The GDEM covers the earth's surface between 83°S and 83°N latitudes (Tachikawa et al. 2011).
A comparative estimate of air temperature from modis land surface temperatures in Ghana
Published in Cogent Engineering, 2023
Adubofour Frimpong, Eric Kwabena Forkuo, Edward Matthew Osei
National Aeronautics and Space Administration (NASA’s) earth observation satellites enable a comprehensive set of measurements to improve our understanding of the earth system. The Moderate Resolution Imaging Spectroradiometer (MODIS) is a satellite-based visible/infrared spectroradiometer on-board the Earth Observing System Satellites (Terra and Aqua) to sense radiation of terrestrial, atmospheric, and oceanic phenomena. They are polar-orbiting satellites and MODIS acquire data in 36 spectral bands, which provide important information for many research applications, including oceans and atmospheres (Dugord & Planning, 2013; Luo et al., 2018).