Utilizing Multi-Temporal Thermal Data To Assess Environmental Land Degradation Impacts: Example From Suez Canal Region, Egypt.

Land surface temperature (LST) analysis of Satellite data is critical for studying the impacts of geo-environmental, hydrometeorological, and land degradation. However, challenges arise to resolve the LST and ground field data resulting from the constant development of land use and land cover (LULC). This study aims to monitor, analyze, assess, and map the environmental land degradation impacts utilizing image processing and GIS tools of space-borne thermal data and fieldwork. Two thermal and optical sets of multi-temporal Landsat TM+5 and TIRS+8 satellite data dated 1984 and 2018 were used to test, detect, and map the thermal and LULC change and their land degradation in the Suez Canal region (SCR). The LULC classification was categorized into seven classes: water bodies, urban, agricultural land, barren land, wetland, clay, and salt crust. LULC and LST change detection and mapping results revealed that the impervious surface, industrial area, saline soil, and urban area have high LST, while wetlands, vegetation cover, and water bodies suffered low LST. The spectral, LST profiles and statistical analyses examined the association between LST and LULC deriving factors. The cluster analyses defined the relationship between LST and LC patterns at the LU level, where the fast transformation of LULC had significant changes in LST. According to these analyses and the fieldwork observations, the SCR was divided into six main areas. These areas vary in LST in association with land degradation and hydro-environmental impacts such as rising groundwater levels, salt accumulation, active seismic fault zones, water pollution, and urban and agricultural activities.

Global Commodity Markets, Chinese Demand for Maize, and Deforestation in Northern Myanmar

This paper makes a significant contribution to understanding the logic of deforestation in Northern Myanmar and connects global trends and regional political economy with local environmental changes. Methodologically, through a combination of remote sensing GIS analysis, for which we use a newly available Myanmar Forest Change dataset produced by TerraPulse and the Smithsonian Conservation Biology Institute, as well as on-the-ground field research observations and interviews with farmers, this paper examines how the expansion of maize plantations in the northern part of Myanmar has implications for deforestation in the region. It argues that a combination of global commodity price shock around 2011–2012 plus easy market access to China generated strong incentives for local farmers to increase the cultivation of maize. The paper contributes to how we understand the environmental impacts of Chinese demands for agricultural products in Southeast Asia.

Agricultural soil fertility properties in the near infrared spectrum

Soil spectrum in the near infrared (NIR) wavelength region can be used to reveal fertility properties which is related to plant cultivations. The main purpose of this presented paper is to study the soil spectrum in the NIR region and its related to the fertility properties in form of heavy metals like Fe and Cu. Soil samples were obtain from several land-use including agriculture, mining and ground field. Near infrared spectrum of soil samples were acquired in wavelength range from 1000 to 2500 nm. Prediction models used to determine Fe and Cu were built by means of partial least squares regression (PLSR) followed by leverage cross validation. Prediction performance was evaluated using coefficient of determination (r2) and ratio of prediction to deviation (RPD). The results showed that both Fe and Cu can be revealed simultaneously using the NIR spectrum with maximum r2 and RPD indexes were 0.93 and 3.86 for Fe and 0.71 and 1.88 for Cu prediction respectively. Based on the achieved results, it may conclude that soil fertility properties can be revealed simultaneously and rapidly using mear infrared spectral data.

Topographic Survey and Modelling using Photogrammetry: A Comparison against Electronic Distance Measurement (EDM) Method

Topographic surveying has been an important companion to the civil engineer in the development of human civilization since ancient history. It is used to map terrestrial features on the ground along with its contour heights. Application of this can be seen in the establishing land boundaries and setting out construction projects. Conventional methods of surveying range from ground field methods such as the use of total station to aerial surveys such as photogrammetry or LiDAR. This study looks to assess the feasibility of aerial photogrammetry using UAVs as a replacement to the conventional EDM survey using total stations. This objective was achieved by carrying out both photogrammetric and EDM surveys on a 350m long stretch of highway. The resulting survey data were processed to produce two comparative TIN surfaces of the highway which were then superimposed together and compared for accuracy. It could be observed that on plan view, both surfaces were quite closely matched with a maximum difference of less than 0.4m and a low standard deviation. In elevation view, however, the differences were larger with maximums of 5.0m, accompanied by large standard deviations. RMS error analysis carried out also correlate with the findings.

Field Effectiveness of Drones to Identify Potential Aedes aegypti Breeding Sites in Household Environments from Tapachula, a Dengue-Endemic City in Southern Mexico

Aedes aegypti control programs require more sensitive tools in order to survey domestic and peridomestic larval habitats for dengue and other arbovirus prevention areas. As a consequence of the COVID-19 pandemic, field technicians have faced a new occupational hazard during their work activities in dengue surveillance and control. Safer strategies to monitor larval populations, in addition to minimum householder contact, are undoubtedly urgently needed. Drones can be part of the solution in urban and rural areas that are dengue-endemic. Throughout this study, the proportion of larvae breeding sites found in the roofs and backyards of houses were assessed using drone images. Concurrently, the traditional ground field technician’s surveillance was utilized to sample the same house groups. The results were analyzed in order to compare the effectiveness of both field surveillance approaches. Aerial images of 216 houses from El Vergel village in Tapachula, Chiapas, Mexico, at a height of 30 m, were obtained using a drone. Each household was sampled indoors and outdoors by vector control personnel targeting all the containers that potentially served as Aedes aegypti breeding sites. The main results were that the drone could find 1 container per 2.8 found by ground surveillance; however, containers that were inaccessible by technicians in roofs and backyards, such as plastic buckets and tubs, disposable plastic containers and flowerpots were more often detected by drones than traditional ground surveillance. This new technological approach would undoubtedly improve the surveillance of Aedes aegypti in household environments, and better vector control activities would therefore be achieved in dengue-endemic countries.

ON FORMAL DEGREES OF UNIPOTENT REPRESENTATIONS

Let G be a reductive p-adic group which splits over an unramified extension of the ground field. Hiraga, Ichino and Ikeda [24] conjectured that the formal degree of a square-integrable G-representation $\pi $ can be expressed in terms of the adjoint $\gamma $ -factor of the enhanced L-parameter of $\pi $ . A similar conjecture was posed for the Plancherel densities of tempered irreducible G-representations. We prove these conjectures for unipotent G-representations. We also derive explicit formulas for the involved adjoint $\gamma $ -factors.

RECIPROCITY SHEAVES AND THEIR RAMIFICATION FILTRATIONS

We define a motivic conductor for any presheaf with transfers F using the categorical framework developed for the theory of motives with modulus by Kahn, Miyazaki, Saito and Yamazaki. If F is a reciprocity sheaf, this conductor yields an increasing and exhaustive filtration on $F(L)$ , where L is any henselian discrete valuation field of geometric type over the perfect ground field. We show that if F is a smooth group scheme, then the motivic conductor extends the Rosenlicht–Serre conductor; if F assigns to X the group of finite characters on the abelianised étale fundamental group of X, then the motivic conductor agrees with the Artin conductor defined by Kato and Matsuda; and if F assigns to X the group of integrable rank $1$ connections (in characteristic $0$ ), then it agrees with the irregularity. We also show that this machinery gives rise to a conductor for torsors under finite flat group schemes over the base field, which we believe to be new. We introduce a general notion of conductors on presheaves with transfers and show that on a reciprocity sheaf, the motivic conductor is minimal and any conductor which is defined only for henselian discrete valuation fields of geometric type with perfect residue field can be uniquely extended to all such fields without any restriction on the residue field. For example, the Kato–Matsuda Artin conductor is characterised as the canonical extension of the classical Artin conductor defined in the case of a perfect residue field.

On the lengths of group algebras of finite abelian groups in the modular case

In this paper, we address the question of finding the length of group algebras of finite abelian groups in the case when the characteristic of the ground field divides the order of the group. We evaluate the exact length for an arbitrary abelian [Formula: see text]-group. For other groups we provide upper and lower bounds for the length of their group algebras.

Control of Palmer Amaranth (Amaranthus palmeri) Regrowth Following Failed Applications of Glufosinate and Fomesafen

Rapid vegetative growth and adverse application conditions are common factors leading to the failure of postemergence herbicides on Palmer amaranth. A sequential herbicide application, or respray, is often necessary to control weeds that have survived the initial herbicide application to protect crop yield and minimize weed seed production. The optimum timing after the initial application and the most effective herbicide for control of Palmer amaranth has not been characterized. The objectives of these experiments were to determine the optimum herbicide for treating Palmer amaranth regrowth, the optimum timing for each of those herbicides, and how the initial failed herbicide might affect efficacy of a second herbicide application. Bare ground field experiments were performed in 2017 and 2018 in which glufosinate or fomesafen herbicide failure was induced on Palmer amaranth plants that were 30 cm in height. Respray treatments of glufosinate, fomesafen, lactofen, 2,4-D, and dicamba were applied once at timings of 4 to 5 days, 7 days, or 11 days after the initial spray application. Nearly all herbicide treatment and timing combinations increased control by at least 13 percentage points compared to no respray herbicide treatment. Regardless of initial herbicide, glufosinate applied as a respray treatment was the most consistent and efficacious with up to 97% control. The specific herbicide used in the second application impacted final weed control more so than timing of the respray application. For instance, control by glufosinate respray treatments was 10 to 18 percentage points greater than control from lactofen respray treatments, whereas control decreased by 3 percentage points when respray applications of any herbicide were made 11 days after initial application of glufosinate compared to 4 to 5 and 7 days after initial application of glufosinate. In the event of failure to control Palmer amaranth with glufosinate or fomesafen, glufosinate should be applied in order to maximize control.

Forest Aboveground Biomass Estimation Using Multi-Features Extracted by Fitting Vertical Backscattered Power Profile of Tomographic SAR

Forest aboveground biomass (AGB), which plays an important role in the study of global carbon cycle, is one of the most important indicators in forest resource monitoring. Thus, how to estimate and map regional forest AGB quickly and accurately attracts more interests of researchers. Tomographic SAR (TomoSAR) is an advanced SAR technique developed in recent years, which has a wide range application in forest AGB estimation. In this paper, we proposed a multi-feature-based modeling method to estimate forest AGB by fitting backscattered power of TomoSAR vertical profile. The procedure of the proposed method includes four parts: (1) Processing TomoSAR data to obtain the backscattered power of vertical profile. (2) Fitting the backscattered power of the vertical profile. (3) Analyzing the fitted backscattered power distribution characteristic of the vertical profile. (4) Extracting the TomoSAR vertical profile features according to the forest AGB measurement factors based on the dendrometry theory. In this paper, we proposed two new features like the forest average height weighted by backscattered power (BPFAH) and the total length of the backscattered power curve (LBPC) as supplement features to estimate forest AGB by TomoSAR technique. We also used the traditional TomoSAR features including backscattered power at specific height layer of vertical power profile (BPV) and forest average height (FAH) for AGB estimation. After the feature selection, the selected features and the ground field data of the forest AGB were used for regression and modeling. Then the forest AGB was estimated and the accuracy was validated. The results showed that the accuracy of proposed method is 90.73%, and RMSE is 42.45 t/ha. Finally, we discussed the performance of our proposed method compared with traditional methods.