VENµS-Derived NDVI and REIP at Different View Azimuth Angles

The bidirectional reflectance distribution function (BRDF) is crucial in determining the quantity of reflected light on the earth’s surface as a function of solar and view angles (i.e., azimuth and zenith angles). The Vegetation and ENvironment monitoring Micro-Satellite (VENµS) provides a unique opportunity to acquire data from the same site, with the same sensor, with almost constant solar and view zenith angles from two (or more) view azimuth angles. The present study was aimed at exploring the view angles’ effect on the stability of the values of albedo and of two vegetation indices (VIs): the normalized difference vegetation index (NDVI) and the red-edge inflection point (REIP). These products were calculated over three polygons representing urban and cultivated areas in April, June, and September 2018, under a minimal time difference of less than two minutes. Arithmetic differences of VIs and a change vector analysis (CVA) were performed. The results show that in urban areas, there was no difference between the VIs, whereas in the well-developed field crop canopy, the REIP was less affected by the view azimuth angle than the NDVI. Results suggest that REIP is a more appropriate index than NDVI for field crop studies and monitoring. This conclusion can be applied in a constellation of satellites that monitor ground features simultaneously but from different view azimuth angles.

Leveraging autoencoders in change vector analysis of optical satellite images

Various applications in remote sensing demand automatic detection of changes in optical satellite images of the same scene acquired over time. This paper investigates how to leverage autoencoders in change vector analysis, in order to better delineate possible changes in a couple of co-registered, optical satellite images. Let us consider both a primary image and a secondary image acquired over time in the same scene. First an autoencoder artificial neural network is trained on the primary image. Then the reconstruction of both images is restored via the trained autoencoder so that the spectral angle distance can be computed pixelwise on the reconstructed data vectors. Finally, a threshold algorithm is used to automatically separate the foreground changed pixels from the unchanged background. The assessment of the proposed method is performed in three couples of benchmark hyperspectral images using different criteria, such as overall accuracy, missed alarms and false alarms. In addition, the method supplies promising results in the analysis of a couple of multispectral images of the burned area in the Majella National Park (Italy).

REMOTE SENSING AND MODELING TOOLS EXPLORATION FOR HABITAT DELIMITATION OF LEISHMANIASIS TRANSMITTING VECTORS

Leishmaniasis encompasses a group of vector-borne parasitic diseases, characterized by their diversity and complexity, that affect both humans and other vertebrates. They are caused by different species of parasites of the Leishmania genus, which are transmitted by bites from hematophagous female sandflies. This work proposed to model the occurrence probability of five sandflies species of sanitary interest for South America, from a bibliographic compilation of records of the last 10 years. To develop the model, the free software MaxEnt was used. This exploratory analysis made it possible to visualize the areas where the species are distributed. In addition, we analyzed land changes in vegetation around a town in Jujuy province, Argentina, where a leishmaniasis outbreak occurred during the years 2017 and 2018. For this, Sentinel-2 images were used, and a change vector was calculated for the difference between two dates of the Normalized Difference Vegetation Index (NDVI). This part of the work was made using SNAP software for images pre-procesing, Python for the change vector obtention and QGIS for the result post-procesing. From the exploration of MaxEnt software we were able to know the most suitable places for the distribution of the most important five species in the study region, and therefore, to project future decision-making to prevent and control leishmaniasis transmission. And in turn, obtain an approximation of how anthropogenic activities, as deforestation, can have an influence on leishmaniasis specific outbreaks transmitted by these species. Finally, from the exploration of the different tools used in this work, the importance of validation with field data for the generation of accurate analyses and predictions is highlighted. It implies that more data collection is necessary to validate the models and analyzes generated, to guarantee the contribution of the tools in macro-ecological studies of species linked to disease transmission.

Evaluating the impacts of major cyclonic catastrophes in coastal Bangladesh using geospatial techniques

Cyclonic catastrophes frequently devastate coastal regions of Bangladesh that host around 35 million people which represents two-thirds of the total population. They have caused many problems like agricultural crop loss, forest degradation, damage to built-up areas, river and shoreline changes that are linked to people’s livelihood and ecological biodiversity. There is an absence of a comprehensive assessment of the major cyclonic disasters of Bangladesh that integrates geospatial technologies in a single study. This study aims to integrate geospatial technologies with major disasters and compares them, which has not been tried before. This paper tried to identify impacts that occurred in the coastal region by major catastrophic events at a vast level using different geospatial technologies. It focuses to identify the impacts of major catastrophic events on livelihood and food production as well as compare the impacts and intensity of different disasters. Furthermore, it compared the losses among several districts and for that previous and post-satellite images of disasters that occurred in 1988, 1991, 2007, 2009, 2019 were used. Classification technique like machine learning algorithm was done in pre- to post-disaster images. For quantifying change in the indication of different factors, indices including NDVI, NDWI, NDBI were developed. “Change vector analysis” equation was performed in bands of the images of pre- and post-disaster to identify the magnitude of change. Also, crop production variance was analyzed to detect impacts on crop production. Furthermore, the changes in shallow to deep water were analyzed. There is a notable change in shallow to deep water bodies after each disaster in Satkhira and Bhola district but subtle changes in Khulna and Bagerhat districts. Change vector analysis revealed greater intensity in Bhola in 1988 and Satkhira in 1991. Furthermore, over the years 2007 and 2009 it showed medium and deep intense areas all over the region. A sharp decrease in Aus rice production is witnessed in Barishal in 2007 when cyclone “Sidr” was stricken. The declination of potato production is seen in Khulna district after the 1988 cyclone. A huge change in the land-use classes from classified images like water body, Pasture land in 1988 and water body, forest in 1991 is marked out. Besides, a clear variation in the settlement was observed from the classified images. This study explores the necessity of using more geospatial technologies in disastrous impacts assessment around the world in the context of Bangladesh and, also, emphasizes taking effective, proper and sustainable disaster management and mitigation measures to counter future disastrous impacts.

Application Biplot Analysis on Mapping of Non-Convertive Diseases in Indonesia

Non-communicable diseases is diseases that are not caused by germs but rather because of physiological or metabolic problems in human body tissues. Usually, this disease occurs due to unhealthy lifestyle. One way to find out how large the spread of non-communicable diseases is by mapping the disease using biplot analysis. Biplot analysis is applied to determine the proximity information between objects, the length of the change vector, the correlation between modifiers, and the value of the change in an object. The study was conducted in 33 provinces with twelve non-communicable diseases. Descriptive analysis of twelve non-communicable diseases averaged the highest joint disease of 10.51 followed by hypertensive disease 8.85 and Stroke 6.42. While the lowest average disease is Heart Failure disease by 0.10 it is still open to research with other methods and also need to add supporting variables

Screening of Influenza a (H1N1) Neuraminidase Inhibitor for Kabasura Kudineer, Nilavembu Kudineer and the Novel Formulation JACOM

<p>Due to erratic climate change, vector-borne diseases started flaring up from the second half of the last decade. Siddha medicine has been used as a public health tool to effectively manage chikungunya and dengue in the epidemics that happened in 2008 and 2016. Tamil Nadu government has made enormous efforts to control vector-borne diseases. Due to which morbidity and mortality due to vector borne diseases came down compared with other states. Two official Siddha formulations, namely Kabasura Kudineer Chooranam and Nilavembu Kudineer Chooranam and novel herbal formulation – JACOM, are used to combat vector-borne diseases. These decoctions lack an evidence base as a formulation. Screening has been done to check the efficacy of the formulation in inhibiting neuraminidase. Neuraminidase inhibition assay was performed to determine the activity of Siddha formulations. The Kabasura Kudineer Chooranam, Nilavembu Kudineer Chooranam and JACOM showed excellent inhibitory activity. The Kabasura Kudineer and Nilavembu Kudineer and JACOM aqueous extract showed maximum neuraminidase inhibition of 80.35%, 91.78% and 87.97%, respectively.</p>

Screening of Influenza a (H1N1) Neuraminidase Inhibitor for Kabasura Kudineer, Nilavembu Kudineer and the Novel Formulation JACOM

<p>Due to erratic climate change, vector-borne diseases started flaring up from the second half of the last decade. Siddha medicine has been used as a public health tool to effectively manage chikungunya and dengue in the epidemics that happened in 2008 and 2016. Tamil Nadu government has made enormous efforts to control vector-borne diseases. Due to which morbidity and mortality due to vector borne diseases came down compared with other states. Two official Siddha formulations, namely Kabasura Kudineer Chooranam and Nilavembu Kudineer Chooranam and novel herbal formulation – JACOM, are used to combat vector-borne diseases. These decoctions lack an evidence base as a formulation. Screening has been done to check the efficacy of the formulation in inhibiting neuraminidase. Neuraminidase inhibition assay was performed to determine the activity of Siddha formulations. The Kabasura Kudineer Chooranam, Nilavembu Kudineer Chooranam and JACOM showed excellent inhibitory activity. The Kabasura Kudineer and Nilavembu Kudineer and JACOM aqueous extract showed maximum neuraminidase inhibition of 80.35%, 91.78% and 87.97%, respectively.</p>