scholarly journals Mapping of Winter Wheat Using Sentinel-2 NDVI Data. A Case of Mashonaland Central Province in Zimbabwe

2021 ◽  
Vol 3 ◽  
Author(s):  
Fadzisayi Mashonganyika ◽  
Hillary Mugiyo ◽  
Ezekia Svotwa ◽  
Dumisani Kutywayo
Keyword(s):  
Remote Sensing ◽  
Early Warning ◽  
Confusion Matrix ◽  
Area Under The Curve ◽  
Warning System ◽  
Decision Makers ◽  
Early Action ◽  
Ground Truthing ◽  
Agriculture Extension ◽  
Sentinel 2

A robust early warning system can alert to the presence of food crises and related drivers, informing decision makers on food security. To date, decision-makers in Zimbabwe still rely on agriculture extension personnel to generate information on wheat production and monitor the crop. Such traditional methods are subjective, costly and their accuracy depends on the experience of the assessor. This study investigates Sentinel-2 NDVI and time series utility as a wheat-monitoring tool over the wheat-growing areas of Zimbabwe's Bindura, Shamva, and Guruve districts. NDVI was used to classify and map the wheat fields. The classification model's evaluation was done by creating 100 reference pixels across the classified map and constructing a confusion matrix with a resultant kappa coefficient of 0.89. A sensitivity test, receiver operating characteristic (ROC) and area under the curve (AUC) were used to measure the model's efficiency. Fifty GPS points randomly collected from wheat fields in the selected districts were used to identify and compute the area of the fields. The correlation between the area declared by farmers and the calculated area was positive, with an R2 value of 0.98 and a Root Mean Square Error (RMSE) of 2.23 hectares. The study concluded that NDVI is a good index for estimating the area under wheat. In this regard, NDVI can be used for early warning and early action, especially in monitoring programs like ‘Command Agriculture’ in Zimbabwe. In current and future studies, the use of high-resolution images from remote sensing is essential. Furthermore, ground truthing is always important to validate results from remote sensing at any spatial scale.

The Bolivian Drought Monitor: an operational tool, calibrated on impact records, to identify and communicate drought severity conditions.

2021 ◽  
Author(s):  
Lauro Rossi ◽  
Alessandro Masoero ◽  
Anna Mapelli ◽  
Fabio Castelli
Keyword(s):  
Remote Sensing ◽  
Early Warning ◽  
Warning System ◽  
Drought Severity ◽  
Severe Drought ◽  
Drought Event ◽  
Context Analysis ◽  
Management Platform ◽  
Drought Conditions ◽  
Civil Defence

<p>Within the framework of the CIF financed “Pilot Program for Climate Resilience”, the Drought Monitoring and Early Warning System for Bolivia was developed and implemented. The system is operational since July 2020 and aims at detecting emerging severe drought conditions in the country, in order to trigger timely warnings to stakeholders and the general public.</p><p>The Bolivian Drought Monitor has two main components: a technical one (data gathering and analysis, performed through the multi-hazard early warning “myDEWETRA” platform) and an institutional one (creating consensus and disseminating warnings). The system design followed a participatory approach, involving since the early stages the Ministry for Water and Environment (MMAyA), the National Hydrometeorological Service (SENAMHI), the Vice-Ministry for Civil Defence (VIDECI). These institutions actively contribute to the monthly edition of the drought bulletin, each one for its own sector of competence, through a dedicated IT tool for synchronous compilation. Ongoing drought conditions are reported in a national bulletin, issued monthly and published on a dedicated public website: http://monitorsequias.senamhi.gob.bo/</p><p>Given the Bolivian data-poor context, analysis strongly relies on a large variety of multi-source satellite products, spanning from well consolidated ones in the operational practice to more experimental ones such as from the SMAP mission. This information is used to monthly refresh the spatial maps of 17 indexes covering meteorological, hydrological and agricultural droughts for different aggregation periods (from 1 to 12 months). Simulation of the system performance over a long period (2002-2019) and comparison with recorded socio-economic drought impacts  from the National Disaster Observatory (Observatorio Nacional de Desastres- OND) of the Vice-Ministry of Civil Defence (VIDECI) was used to define a most representative compound index, based on a weighted combination of a selection of 4 indexes with their related thresholds. The combination of 3-month SPEI, 2-month SWDI, 1-month VHI and 1-month FAPAR indexes performed the best in the comparison with impact records. This combination encompasses both the medium-term effects of meteorological and hydrological deficits (3-month SPEI and SWDI), both the short-term effects on vegetation (1-month VHI and FAPAR). This set of indexes proved to be a solid proxy in estimating possible impacts on population of ongoing or incoming drought spells, as happened for most significant recent drought events occurred in Bolivia, such as the 2010 event in the Chaco region and the 2016 drought event in the Altiplano and Valles regions, that heavily affected the water supply in several major cities (La Paz, Sucre, Cochabamba, Oruro and Potosí).</p><p>The design of the monitoring and bulletin management platform, together with its strong remote-sensing base, give to the system a high potential for easy export to other regional and national contexts. Also, the variety of the different computed drought indexes and the replicability of the procedure for the best compound index identification will allow for efficient evolutionary maintenance as new remote-sensing products will be available in the future.</p>

scholarly journals Communication Structures and Decision Making Cues and Criteria to Support Effective Drought Warning in Central Malawi

2020 ◽  
Vol 2 ◽  
Author(s):  
Alexia Calvel ◽  
Micha Werner ◽  
Marc van den Homberg ◽  
Andrés Cabrera Flamini ◽  
Ileen Streefkerk ◽  
...  
Keyword(s):  
Decision Making ◽  
Early Warning ◽  
Warning System ◽  
Agricultural Practices ◽  
Early Warning Systems ◽  
Sudden Onset ◽  
Small Scale ◽  
Warning Systems ◽  
Structured Interviews ◽  
Early Action

Early warning systems trigger early action and enable better disaster preparedness. People-centered dissemination and communication are pivotal for the effective uptake of early warnings. Current research predominantly focuses on sudden-onset hazards, such as floods, ignoring considerable differences with slow-onset hazards, such as droughts. We identify the essential factors contributing to effective drought dissemination and communication using the people-centered approach advocated in the WMOs Multi-Hazard Early Warning System Framework (MHEWS). We use semi-structured interviews with key stakeholders and focus group discussions with small-scale farmers in the Mangochi and Salima Districts of Malawi. We show that the timely release of seasonal forecast, the tailoring of the drought warning content (and its timing) to agricultural decision making, and the provision of several dissemination channels enhance trust and improve uptake of drought warning information by farmers. Our analysis demonstrates that farmers seek, prepare, and respond to drought warning information when it is provided as advice on agricultural practices, rather than as weather-related information. The information was found to be useful where it offers advice on the criteria and environmental cues that farmers can use to inform their decisions in a timely manner. Based on our findings, we propose that by focusing on enhancing trust, improving information uptake and financial sustainability as key metrics, the MHEWS can be adapted for use in monitoring the effectiveness of early warning systems.

On the development and operationalization of an impact-based forecasting system to support early action for river floods in Zambia

2020 ◽  
Author(s):  
Stefania Giodini ◽  
Aklilu Teklesadik ◽  
Jannis Visser ◽  
Orla Canavan ◽  
Innocent Bwalya ◽  
...  
Keyword(s):  
Early Warning ◽  
Situational Awareness ◽  
Warning System ◽  
Secondary Data ◽  
Emergency Operation ◽  
Lessons Learned ◽  
Red Cross ◽  
Early Action ◽  
Local Decision ◽  
The Impact

<div>Flooding in Zambia occurs on almost an annual basis greatly affecting the livelihoods of communities. Early action is crucial to mitigate the impact of flooding but needs to be guided by an early warning that is credible and actionable, linked to situational awareness based on data.  The 510 data team at the Netherlands Red Cross has been working together with the Red Cross Red Crescent Climate Centre, Zambia Red Cross Society, Water Resources Management Authority (WARMA) and Zambia Disaster Management and Mitigation Unit (DMMU) to develop a data driven early warning system to support impact based early action implementation. The system has been co-designed with the relevant local stakeholders and  integrates a hydrological model with a vulnerability capacity assessment based on secondary data for the whole country at the highest level of possible granularity (district level). A threshold based trigger model has been developed together with local decision makers to activate the system with a lead time up to 7 days. The system is being integrated in the Emergency Operation Centre operated by Zambia's DMMU as a part of the country standard early action protocol. This paper describes the system design, results from the first activations and lessons learned. </div>

scholarly journals Communicating Complex Forecasts for Enhanced Early Warning in Nepal

2019 ◽  
Author(s):  
Mirianna Budimir ◽  
Amy Donovan ◽  
Sarah Brown ◽  
Puja Shakya ◽  
Dilip Gautam ◽  
...  
Keyword(s):  
Early Warning ◽  
Lead Time ◽  
Warning System ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Time Data ◽  
Deterministic Models ◽  
Early Action ◽  
Probabilistic Forecasts ◽  
Barriers And Challenges

Abstract. Early warning systems have the potential to save lives and improve resilience. Simple early warning systems rely on real-time data and deterministic models to generate evacuation warnings; these simple deterministic models enable life-saving action, but provide limited lead time for resilience-building early action. More complex early warning systems supported by forecasts, including probabilistic forecasts, can provide additional lead time for preparation. However, barriers and challenges remain in disseminating and communicating these more complex warnings to community members and individuals at risk. Research was undertaken to analyse and understand the current early warning system in Nepal, considering available data and forecasts, information flows, early warning dissemination and decision making for early action. The research reviewed the availability and utilisation of complex forecasts in Nepal, their integration into dissemination (Department of Hydrology and Meteorology (DHM) bulletins and SMS warnings), and decision support tools (Common Alerting Protocols and Standard Operating Procedures), considering their impact on improving early action to increase the resilience of vulnerable communities to flooding.

scholarly journals Identification of a Threshold Minimum Area for Reflectance Retrieval from Thermokarst Lakes and Ponds Using Full-Pixel Data from Sentinel-2

2019 ◽  
Vol 11 (6) ◽  
pp. 657 ◽  
Author(s):  
Pedro Freitas ◽  
Gonçalo Vieira ◽  
João Canário ◽  
Diogo Folhas ◽  
Warwick Vincent
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Lake Area ◽  
Small Lakes ◽  
Thermokarst Lakes ◽  
High Resolution Imagery ◽  
Complementary Approach ◽  
Boundary Definition ◽  
Ground Truthing ◽  
Sentinel 2

Thermokarst waterbodies caused by permafrost thawing and degradation are ubiquitous in many subarctic and Arctic regions. They are globally important components of the biogeochemical carbon cycle and have potential feedback effects on climate. These northern waters are mostly small lakes and ponds, and although they may be mapped using very high-resolution satellites or aerial photography, these approaches are generally not suitable for monitoring purposes, due to the cost and limited availability of such images. In this study we evaluated the potential use of widely available high-resolution imagery from Sentinel-2 (S2) for the characterization of the spectral reflectance of thermokarst lakes and ponds. Specifically, we aimed to define the minimum lake area that could be reliably imaged, and to identify challenges and solutions for remote sensing of such waters in the future. The study was conducted in subarctic Canada, in the vicinity of Whapmagoostui-Kuujjuarapik (Nunavik, Québec), an area in the sporadic permafrost zone with numerous thermokarst waterbodies that vary greatly in size. Ground truthing lake reflectance data were collected using an Unmanned Aerial System (UAS) fitted with a multispectral camera that collected images at 13 cm resolution. The results were compared with reflectance from Sentinel-2 images, and the effect of lake area on the reflectance response was assessed. Our results show that Sentinel-2 imagery was suitable for waterbodies larger than 350 m2 once their boundaries were defined, which in the two test sites would allow monitoring from 11% to 30% of the waterbodies and 73% to 85% of the total lake area. Challenges for remote sensing of small lakes include the confounding effects of water reflection (both direct radiation and diffuse), wind and shadow. Given the small threshold area and frequent revisit time, Sentinel-2 provides a valuable approach towards the continuous monitoring of waterbodies, including ponds and small lakes such as those found in thermokarst landscapes. UASs provide a complementary approach for ground truthing and boundary definition.

Towards improving a national flood early warning system with global ensemble flood predictions and local knowledge; a case study on the Lower Shire Valley in Malawi.

2020 ◽  
Author(s):  
Thirza Teule ◽  
Anaïs Couasnon ◽  
Kostas Bischiniotis ◽  
Julia Blasch ◽  
Marc van den Homberg
Keyword(s):  
Local Knowledge ◽  
Early Warning ◽  
Flood Risk ◽  
National Level ◽  
Warning System ◽  
Early Warning Systems ◽  
Structured Interviews ◽  
Early Action ◽  
Disastrous Flood

<p>Flood risk, a function of hazard, exposure, and vulnerability, is increasing globally and has led to more and more disastrous flood events. Previous research has shown that taking early action is much more cost-effective than responding once the flood occurs. Such an anticipatory approach requires flood early warning systems (EWS) that provide ample lead time and that have sufficient spatial resolution. However, in developing countries, often the skill of available forecasts is insufficient to create a more effective triggering mechanism as part of a flood EWS.</p><p>This research presents an assessment of two methods to improve an existing flood EWS using a case study of the most flood-prone area of Malawi, i.e. the Lower Shire Valley. First, the forecast skill and trigger levels of the medium-term Global Flood Awareness System (GloFAS) model are determined for four gauge locations to assess how they can improve the national EWS. Secondly, an assessment is done on how the process of integrating flood forecasts based on local knowledge with official forecasts, can help to improve the EWS. This is done by semi-structured interviews at the national level and focus group discussions at the community level. The study shows that GloFAS does not predict absolute discharge values precisely, but can be used to predict floods if the correct trigger levels are set per location. The integration of multiple forecast sources is found to be useful at both national and community levels. An integration process is proposed where village stakeholders should take the leading role by using existing disaster management and civil protection coordination mechanisms. Overall, both methods can contribute to improving the flood EWS and decreasing the flood risk in the Lower Shire Valley in Malawi.</p>

scholarly journals The Niguarda MEWS, a new and refined tool to determine criticality and instability in Internal Medicine Ward and Emergency Medicine Unit

2017 ◽  
Vol 11 (3) ◽  
pp. 310
Author(s):  
Fabrizio Colombo ◽  
Lucia Taurino ◽  
Giulia Colombo ◽  
Massimo Amato ◽  
Salvatore Rizzo ◽  
...  
Keyword(s):  
Internal Medicine ◽  
Early Warning ◽  
Primary Outcome ◽  
Area Under The Curve ◽  
Warning System ◽  
Early Warning Score ◽  
Secondary Outcome ◽  
Internal Medicine Ward ◽  
Level Of Consciousness ◽  
The Right

This study compares the effect of the modified early warning score (MEWS) <em>versus</em> a new early warning system (Niguarda MEWS) for detecting instability and criticality in hospital medical departments. A retrospective observational study was conducted in the Internal Medicine ward of Niguarda Ca’ Granda Hospital in Milan between November 2013 and October 2014. MEWS and Niguarda-MEWS were gathered using: systolic blood pressure, respiratory frequency, heart rate, temperature, level of consciousness, oxygen saturation, creatinine level, hematocrit level and age. In order to determine if the patient was critical or not the MEWS criticality cut-off value chosen was 3, while in the Niguarda MEWS it was 6. The primary outcome was the correlation between the critical level of the two scores and in-hospital mortality. The secondary endpoint was the correlation between a specific disease and the two scores. In the study, 471 patients were included, using both the MEWS and the Niguarda MEWS score at admittance: 33.4% of patients turned out to be critically ill using the former, 40.98% when using the latter. Therefore, the specificity of scores was 70% for MEWS and 73% for Niguarda MEWS, the sensitivity 58% for MEWS and 63% for Niguarda MEWS, Niguarda MEWS area under the curve (AUC): 0.736, MEWS AUC: 0.670. For the secondary outcome, the new score is higher for genitourinary and respiratory diseases. Niguarda-MEWS could be an optimal tool to detect criticality and instability in order to address the patient to the right level of care.

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