Flood hazards pose a significant threat to communities and ecosystems alike. Triggered by various factors such as heavy rainfall, storm surges, or rapid snowmelt, floods can wreak havoc by inundating low-lying areas and overwhelming infrastructure systems. Understanding the feedback between local geomorphology and sediment transport dynamics in terms of the extent and evolution of flood-related damage is necessary to build a system-level description of flood hazard. In this research, we present a multispectral imagery-based approach to broadly map sediment classes and how their spatial extent and relocation can be monitored. The methodology is developed and tested using data collected in the Ahr Valley in Germany during post-disaster reconnaissance of the July 2021 Western European flooding. Using uncrewed aerial vehicle-borne multispectral imagery calibrated with laboratory-based soil characterization, we illustrate how fine and coarse-grained sediments can be broadly identified and mapped to interpret their transport behavior during flood events and their role regarding flood impacts on infrastructure systems. The methodology is also applied to data from the 2022 flooding of the Yellowstone River, Gardiner, Montana, in the United States to illustrate the transferability of the developed approach across environments. Here, we show how the distribution of soil classes can be mapped remotely and rapidly, and how this facilitates understanding their influence on local flow patterns to induce bridge abutment scour. The limitations and potential expansions to the approach are also discussed.

Agricultural drought significantly affects crop growth and food production, making accurate drought thresholds essential for effective monitoring and discrimination. This study aims to monitor the threshold ranges for different drought levels of winter wheat during three growth periods using a multispectral Unmanned Aerial Vehicle (UAV). Firstly, based on controlled field experiments, six vegetation indices were used to develop UAV optimal inversion models for the Leaf Area Index (LAI) and Soil-Plant Analysis Development (SPAD) during the jointing-heading period, heading-filling period, and filling-maturity period of winter wheat. The results show that during the three growth periods, the DVI-LAI, NDVI-LAI, and RVI-LAI models, along with the DVI-SPAD, RVI-SPAD, and TCARI-SPAD models, achieved the highest inversion accuracy. Based on the UAV-inversed LAI and SPAD indices, threshold ranges for different drought levels were determined for each period. The accuracy of LAI threshold monitoring during three periods was 92.8%, 93.6%, and 90.5%, respectively, with an overall accuracy of 92.4%. For the SPAD index, the threshold monitoring accuracy during three periods was 93.1%, 93.0%, and 92%, respectively, with an overall accuracy of 92.7%. Finally, combined with yield data, this study explores UAV-based drought disaster monitoring for winter wheat. This research enriches and expands the crop drought monitoring system using a multispectral UAV. The proposed drought threshold ranges can enhance the scientific and precise monitoring of crop drought, which is highly significant for agricultural management.

Weed control in agricultural systems is of the utmost importance. Weeds reduce crop yields by up to 30% to 40%. Different methods are used to control weeds, such as manual, chemical, mechanical, and precision weed management. Weeds are managed more effectively by using the hand weeding method, which nevertheless falls short due to the unavailability of labor during peak periods and increasing labor wages. Generally, manual weeding tools have higher weeding efficiency (72% to 99%) but lower field capacity (0.001 to 0.033 hm(2)/h). Use of chemicals to control weeds is the most efficient and cost-effective strategy. Chemical weedicides have been used excessively and inappropriately, which has over time resulted in many issues with food and environmental damage. Mechanical weed control improves soil aeration, increases water retention capacity, slows weed growth, and has no negative effects on plants. Mechanical weed management techniques have been gaining importance recently. Automation in agriculture has significantly enhanced mechanization inputs for weed management. The development of precision weed management techniques offers an efficient way to control weeds, contributing to greater sustainability and improved agricultural productivity. Devices for agricultural automated navigation have been built on the rapid deployment of sensors, microcontrollers, and computing technologies into the field. The automated system saves time and reduces labor requirements and health risks associated with drudgery, all of which contribute to more effective farm operations. The new era of agriculture demands highly efficient and effective autonomous weed control techniques. Methods such as remote sensing, multispectral and hyperspectral imaging, and the use of robots or UAVs (drones) can significantly reduce labor requirements, enhance food production speed, maintain crop quality, address ecological imbalances, and ensure the precise application of agrochemicals. Weed monitoring is made more effective and safer for the environment through integrated weed management and UAVs. In the future, weed control by UAV or robot will be two of the key solutions because they do not pollute the environment or cause plant damage, nor do they compact the soil, because UAV sprays above the ground and robotic machines are lighter than tractor operated machines. This paper aims to review conventional, chemical, mechanical, and precision weed management methods.

Canopy water interception is a key parameter to study the hydrological cycle, water utilization efficiency, and energy balance in terrestrial ecosystems. Especially in sprinkler-irrigated farmlands, the canopy interception further influences field energy distribution and microclimate, then plant transpiration and photosynthesis, and finally crop yield and water productivity. To reduce the field damage and increase measurement accuracy under traditional canopy water interception measurement, UAVs equipped with multispectral cameras were used to extract in situ crop canopy information. Based on the correlation coefficient (r), vegetative indices that are sensitive to canopy interception were screened out and then used to develop canopy interception models using linear regression (LR), random forest (RF), and back propagation neural network (BPNN) methods, and lastly these models were evaluated by root mean square error (RMSE) and mean relative error (MRE). Results show the canopy water interception is first closely related to relative normalized difference vegetation index (R triangle NDVI) with r of 0.76. The first seven indices with r from high to low are R triangle NDVI, reflectance values of the blue band (Blue), reflectance values of the near-infrared band (Nir), three-band gradient difference vegetation index (TGDVI), difference vegetation index (DVI), normalized difference red edge index (NDRE), and soil-adjusted vegetation index (SAVI) were chosen to develop canopy interception models. All the developed linear regression models based on three indices (R triangle NDVI, Blue, and NDRE), the RF model, and the BPNN model performed well in canopy water interception estimation (r: 0.53-0.76, RMSE: 0.18-0.27 mm, MRE: 21-27%) when the interception is less than 1.4 mm. The three methods underestimate the canopy interception by 18-32% when interception is higher than 1.4 mm, which could be due to the saturation of NDVI when leaf area index is higher than 4.0. Because linear regression is easy to perform, then the linear regression method with NDVI is recommended for canopy interception estimation of sprinkler-irrigated winter wheat. The proposed linear regression method and the R triangle NDVI index can further be used to estimate the canopy water interception of other plants as well as forest canopy.

Coal has been crucial in driving economic development and production construction. However, the mining-induced subsidence may cause irreversible damage to the surrounding environment of vegetation growth. Meanwhile, with the worsening of global warming, the frequency and intensity of extreme water-related weather events, such as droughts and excessive rainfall, are on the rise, which leads to heightened impacts on ecosystems and agricultural production. Consequently, extreme water-related weather, the distribution of land subsidence, and its effect on vegetation have attracted significant attention. Based on the Sentinel-1 radar data and Sentinel-2 multispectral data from 2017 to 2022, the SBAS-InSAR technology, the object-oriented classification, and the Normalized Difference Vegetation Index (NDVI) were employed respectively in the study to obtain the spatial-temporal evolution of land subsidence, subsidence-induced water, and crop growth in Tiefa mining area, a representative coal mining area in Northeast China. Moreover, the relationship between land subsidence, subsidence-induced water, and vegetation change was analyzed combined with summer precipitation data. The results showed that: (1) The average cumulative subsidence of the mining area was 256.8 mm, and the subsidence area was 42.525 km2 for the six years. Among them, the heaviest subsidence reached a maximum of 380.5 mm in 2022, and the largest subsidence area was 20.109 km2 in 2017. (2) When the rainfall was excessive, the area of subsidence-induced water would increase sharply, with a proportion jumping to 9.71% from 5.37%, which indicated the subsidence would further amplify the destructive effect of excessive rainfall and waterlogging on land resources. (3) In addition to the existing water pits, ground cracks and shallow subsidence pits appeared under the influence of underground coal mining. The direct impact of ground cracks on crops was not apparent, while the effect of subsidence pits on crops under different rainfall conditions was dual character. In dry years, crops in the subsidence pits could grow better due to higher soil moisture. In wet years, crops in the subsidence pits would suffer the more severe waterlogging. The research results are of great significance for further understanding the influence of coal mining on surface vegetation in mining areas in Northeast China.

Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

PROSPECT is a comprehensive payload package developed by the European Space Agency which will support the extraction and analysis of lunar surface and subsurface samples as well as the acquisition of data from additional environmental sensors. The key elements of PROSPECT are the ProSEED drill and the ProSPA analytical laboratory. ProSEED will support the acquisition of cryogenic samples from depths up to 1 m and deliver them to the ProSPA instrument. ProSPA will receive and seal samples in miniaturized ovens, heat them, physically and chemically process the released volatiles, and analyze the obtained constituents via mass spectrometry using two types of spectrometers. Contextual information will be provided by cameras which will generate multi-spectral images of the drill working area and of acquired samples, and via temperature sensors and a permittivity sensor that are integrated in the drill rod. The package is designed for minimizing volatile loss from the sample between acquisition and analysis. Initially developed for a flight on the Russian Luna-27 mission, the payload package design was adapted for a more generic lander accommodation and will be flown on a lunar polar lander mission developed within the NASA Commercial Lunar Payload Services (CLPS) program. PROSPECT targets science and exploration in lunar areas that might harbor deposits of volatiles, and also supports the demonstration of In-Situ Resource Utilization (ISRU) techniques in the lunar environment. PROSPECT operations are designed to be automated to a significant degree but rely on operator monitoring during critical phases. Here, we report the PROSPECT flight design that will be built, tested, and qualified according to European space technology engineering standards before delivery to the lander provider for spacecraft integration. The package is currently in the hardware manufacturing and integration phase with a target delivery to the NASA-selected CLPS lander provider in 2025.

Lunar Reconnaissance Orbiter (LRO) was launched in 2009 to study and map the Moon and is now completing its fifth extended science mission. The LRO (see Figure 1) hosts a payload of seven different scientific instruments. The Cosmic Ray Telescope for the Effects of Radiation instrument has characterized the lunar radiation environment and allowed scientists to determine potential impacts to astronauts and other life. The Diviner Lunar Radiometer Experiment (DLRE) has identified cold traps where ice could reside and mapped global thermophysical and mineralogical properties by measuring surface and subsurface temperatures. The Lyman Alpha Mapping Project has found evidence of exposed ice in south polar cold traps as well as global diurnal variations in hydration. The Lunar Exploration Neutron Detector has been used to create high-resolution maps of lunar hydrogen distribution and gather information about the neutron component of the lunar radiation environment. The Lunar Reconnaissance Orbiter Camera (LROC) is a system of three cameras [one wide-angle camera and two narrow-angle cameras (NACs)] mounted on the LRO that capture high-resolution black-and-white images and moderate resolution multispectral (seven-color band) images of the lunar surface. These images can be used, for example, to learn new details about the history of lunar volcanism or the present-day flux of impactors. The Miniature Radio Frequency (Mini-RF) instrument is an advanced synthetic aperture radar (SAR) that can probe surface and subsurface coherent rock contents to identify the polarization signature of ice in cold traps. The Lunar Orbiter Laser Altimeter (LOLA) has been used to generate a high-resolution, 3D map of the Moon that serves as the most accurate geodetic framework available for co-locating LRO (and other lunar) data. The data produced by the LRO continue to revolutionize our scientific understanding of the Moon, and are essential to planning NASA's future human and robotic lunar missions.

Non -invasive potato defects detection has been demanded for sorting and grading purpose. Researches on the classification of the defects has been available, however, investigation on the severity level calculation is limited. For the detection of the common scab, it has been found that imaging in the infrared region provide an interesting characteristic that could distinguish defected area to normal area. Thus, investigations on this wavelength range is interesting to add more knowledge and for applications. In this research, the multispectral image has been obtained and investigated especially at three wavelengths (950, 1 150, 1 600 nm). Image pre-processing and pseudo-color conversion techniques were explored to enhance the contrast between defects, normal background skin area and soil deposits. Results show that external defects, such as common scab and some mechanical damage types, appear brighter in the near infrared region, especially at 1600 nm against the normal skin background. It has been found that pseudo-color images conversion provides more information regarding type if surface characteristics compared to grayscale single imaging. Image segmentation using pseudo-color images after multiplication operation preprocessing could be used for common scab and mechanical damage detection excluding soil deposits with a Dice Sorensen coefficient of 0.64. In addition, image segmentation using single image at 1 600 nm shown relatively better results with Dice Sorensen coefficient of 0.72 with note that thick soil deposits will also be segmented. Defect severity level evaluation had an R2 correlation of 0.84 against standard measurements of severity. (c) 2022 China Agricultural University. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY -NC -ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/).

Since leaving Vera Rubin ridge (VRr), the Mars Science Laboratory Curiosity rover has traversed though the phyllosilicate-bearing region, Glen Torridon, and the overlying Mg-sulfate-bearing strata, with excursions onto the Greenheugh Pediment and Amapari Marker Band. Each of these distinct geologic units were investigated using Curiosity's Mast Camera (Mastcam) multispectral instrument which is sensitive to iron-bearing phases and some hydrated minerals. We used Mastcam spectra, in combination with chemical data from Chemistry and Mineralogy, Alpha Particle X-ray Spectrometer, and Chemistry and Camera instruments, to assess the variability of rock spectra and interpret the mineralogy and diagenesis in the clay-sulfate transition and surrounding regions. We identify four new classes of rock spectra since leaving VRr; two are inherent to dusty and pyroxene-rich surfaces on the Amapari Marker Band; one is associated with the relatively young, basaltic, Greenheugh Pediment; and the last indicates areas subjected to intense aqueous alteration with an amorphous Fe-sulfate component, primarily in the clay-sulfate transition region. To constrain the Mg-sulfate detection capabilities of Mastcam and aid in the analyses of multispectral data, we also measured the spectral response of mixtures with phyllosilicates, hydrated Mg-sulfate, and basalt in the laboratory. We find that hydrated Mg-sulfates are easily masked by other materials, requiring >= 90 wt.% of hydrated Mg-sulfate to exhibit a hydration signature in Mastcam spectra, which places constraints on the abundance of hydrated Mg-sulfates along the traverse. Together, these results imply significant compositional changes along the traverse since leaving VRr, and they support the hypothesis of wet-dry cycles in the clay-sulfate transition. The clay-sulfate transition in Gale crater has long been hypothesized to record an environmental shift from warm and wet to cold and dry. The paleolake that once filled Gale crater allowed phyllosilicates to form. As Mars became cooler and drier, sulfates were able to precipitate above the phyllosilicates. This mineralogic transition has been observed in other places on Mars, implying a global environmental change. Different hydrated Mg-sulfates can reveal characteristics of the paleoenvironment at the time of deposition and thus clarify the geologic history. The goals of this study are to (a) characterize potential sulfate-bearing rocks with the Curiosity rover's multispectral imaging instrument, Mastcam; and (b) constrain Mastcam's Mg-sulfate detection threshold using laboratory techniques. We identify three new rock spectral classes inherent to the clay-sulfate transition and one new class associated with the Greeneheugh pediment. Our laboratory results indicate that it would be challenging to detect Mg-sulfate with Mastcam unless it is nearly pure. New rock spectral classes correspond to unique geologic units. One supports the hypothesis of wet-dry cycles in the clay-sulfate transition Cross instrument analyses imply that Mg- and Fe- sulfates are significant in the amorphous component of the clay-sulfate transition region The spectral signature of hydrated Mg-sulfates in visible to near infrared reflectance spectra are easily masked by phyllosilicates and/or basalt