The COVID-19 related lockdowns have brought the planet to a standstill. It has severely shrunk the global economy in the year 2020, including India. The blue economy and especially the small-scale fisheries sector in India have dwindled due to disruptions in the fish catch, market, and supply chain. This research presents the applicability of satellite data to monitor the impact of COVID-19 related lockdown on the Indian fisheries sector. Three harbors namely Mangrol, Veraval, and Vankbara situated on the north-western coast of India were selected in this study based on characteristics like harbor’s age, administrative control, and availability of cloud-free satellite images. To analyze the impact of COVID in the fisheries sector, we utilized high-resolution PlanetScope data for monitoring and comparison of “area under fishing boats” during the pre-lockdown, lockdown, and post-lockdown phases. A support vector machine (SVM) classification algorithm was used to identify the area under the boats. The classification results were complemented with socio-economic data and ground-level information for understanding the impact of the pandemic on the three sites. During the peak of the lockdown, it was found that the “area under fishing boats” near the docks and those parked on the land area increased by 483%, 189%, and 826% at Mangrol, Veraval, and Vanakbara harbor, respectively. After phase-I of lockdown, the number of parked vessels decreased, yet those already moved out to the land area were not returned until the south-west monsoon was over. A quarter of the annual production is estimated to be lost at the three harbors due to lockdown. Our last observation (September 2020) result shows that regular fishing activity has already been re-established in all three locations. PlanetScope data with daily revisit time has a higher potential to be used in the future and can help policymakers in making informed decisions vis-à-vis the fishing industry during an emergency situation like COVID-19.
The Earth's ecosystems face severe environmental stress from unsustainable socioeconomic development linked to population growth, urbanization, and industrialization. Governments worldwide are interested in sustainability measures to address these issues. Remote sensing allows for the measurement, integration, and presentation of useful information for effective decision-making at various temporal and spatial scales. Scientists and decision-makers have endorsed extensive use of remote sensing to bridge gaps among disciplines and achieve sustainable development. This paper presents an extensive review of remote sensing technology used to support sustainable development efforts, with a focus on natural resource management and assessment of natural hazards. We further explore how remote sensing can be used in a cross-cutting, interdisciplinary manner to support decision-making aimed at addressing sustainable development challenges. Remote sensing technology has improved significantly in terms of sensor resolution, data acquisition time, and accessibility over the past several years. This technology has also been widely applied to address key issues and challenges in sustainability. Furthermore, an evaluation of the suitability and limitations of various satellite-derived indices proposed in the literature for assessing sustainable development goals showed that these older indices still perform reasonably well. Nevertheless, with advancements in sensor radiometry and resolution, they were less exploited and new indices are less explored.
Remote sensing technology has seen a massive rise in popularity over the last two decades, becoming an integral part of our lives. Space-based satellite technologies facilitated access to the inaccessible terrains, helped humanitarian teams, support complex emergencies, and contributed to monitoring and verifying conflict zones. The scoping phase of this review investigated the utility of the role of remote sensing application to complement international peace and security activities owing to their ability to provide objective near real-time insights at the ground level. The first part of this review looks into the major research concepts and implementation of remote sensing-based techniques for international peace and security applications and presented a meta-analysis on how advanced sensor capabilities can support various aspects of peace and security. With key examples, we demonstrated how this technology assemblage enacts multiple versions of peace and security: for refugee relief operations, in armed conflicts monitoring, tracking acts of genocide, providing evidence in courts of law, and assessing contravention in human rights. The second part of this review anticipates future challenges that can hinder the applicative capabilities of remote sensing in peace and security. Varying types of sensors pose discrepancies in image classifications and issues like cost, resolution, and difficulty of ground-truth in conflict areas. With emerging technologies and sufficient secondary resources available, remote sensing plays a vital operational tool in conflict-affected areas by supporting an extensive diversity in public policy actions for peacekeeping processes.
Climate change, which encompasses variations in rainfall and temperature patterns, coupled with changes in land use/land cover (LULC), significantly impacts both the environment and society. These two factors, climate change and LULC shifts, have markedly affected human health, both directly and indirectly. Monitoring regional climate patterns, LULC changes, and disease outbreaks is crucial to ensure healthy living standards through a sustainable environment. This study investigates the correlation between climate change, LULC change, and the prevalence of infectious diseases transmitted by vectors and waterborne pathogens in Coimbatore district, Tamil Nadu, India, from 1985 to 2015. The study used Landsat-4, Landsat-5 and Landsat-8 data to generate LULC maps of the study area. The maximum likelihood algorithm facilitated the creation of these maps and detected changes for the years 1985, 2000, 2009, and 2015. Rainfall and temperature data for the study area were sourced from APHRODITE's Water Resources, and statistical analysis was applied to analyse these time series data. Infectious disease data was obtained from the Indian Council of Medical Research (ICMR), the Integrated Disease Surveillance Programme (IDSP), the National Vector Borne Disease Control Programme (NVBDCP), and the National Health System Resource Centre. These data were examined to identify trends in the occurrence of infectious diseases. The key findings of the study include (1) an overall increase in temperature and minor variations in rainfall in the study area during the study period; (2) an evident increase in built-up areas, as depicted by the LULC maps, attributable to industrialisation and population growth; (3) an emergence of dengue during the study period. The increasing patterns of vector-borne and water-borne diseases could be associated with changes in LULC and climate change. Given that the relationship between infectious diseases and their links to climate change and LULC changes has not been extensively researched in the Indian context, this study intends to contribute to a deeper understanding and delineation of future strategies in Coimbatore, India.
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