Mapping small(holder) farms using big data

More than 80% of the world’s farms are defined as smallholder, with field sizes \u3c 2 hectares. This project produced a wall-to-wall cropland area map for the rain-fed residential cropland mosaic of Tigray Region, Ethiopia, which is comprised entirely of smallholder farms. Sub-meter WorldView-1 and WorldView-2 segmentation results were combined with median phenology amplitude from Landsat 8 data to map crop area. The WorldView constellation, operated by DigitalGlobe, images over 1.2 billion km2 annually at \u3c 2 m spatial resolution, producing petabytes of data per year. Due to computation, data cost, and methodological concerns, very high resolution (VHR) satellite data has mainly been used to produce needed geospatial information for site-specific phenomena. Over 2,700 VHR WorldView-1, -2 data were obtained from the U.S. National Geospatial-Intelligence Agency (NGA) via the NextView license agreement and were processed from raw imagery to produce a smallholder crop map in ~1 week using a semi-automated method and large computing capacity of NASA’s Advanced Data Analytics Platform. This methodology is extensible to other regions with similar vegetation and can easily be expanded to country-scale.https://digitalcommons.mtu.edu/techtalks/1042/thumbnail.jp

SEASONAL AND INTERANNUAL VARIABILITY OF EMISSIONS FROM CROP RESIDUE BURNING IN THE CONTIGUOUS UNITED STATES

Crop residue burning is a global agricultural practice used to remove excess residues before or after harvest. Crop residue burning in the contiguous United States (CONUS) has been documented at the regional and state-level by governmental organizations and in the scientific literature. Emissions from crop residue burning in the CONUS have been found to impair local and regional air quality, leading to serious health impacts and legal disputes. Currently, there is no baseline estimate for the area and emissions of crop residue burning in the CONUS. A bottom-up model for emissions calculations is employed to calculate CO2, CO, CH4, NO2, SO2, PM2.5, PM10, and Pb emissions from crop residue burning in the CONUS for the years 2003 through 2007. These atmospheric species have negative impacts on air quality and human health and are important to the carbon cycle. Spatially and temporally explicit cropland burned area and crop type products for the CONUS, necessary for emissions calculations, are developed using remote sensing approaches. The majority of crop residue burning and emissions in the CONUS are shown to occur during the spring (April - June) and fall harvests (October - December). On average, 1,239,000 ha of croplands burn annually in the CONUS with an average interannual variability of ± 91,200 ha. In general, CONUS crop residue burning emissions vary less than ±10% interannually. The states of Arkansas, California, Florida, Idaho, Texas, and Washington emit 50% of PM10, 51% of CO2, 52% of CO, and 63% of PM2.5 from all crop residue burning in the CONUS. Florida alone emits 17% of all annual CO2, CO, and PM2.5 emissions and 12% of annual PM10 emissions from crop residue burning. Crop residue burning emissions in the CONUS account for as little as 1% of global agricultural emissions and as much as 15% of all agricultural burning emissions estimates in North America, including Mexico and Canada. The results have implications for international, federal, and state-level reporting and monitoring of air quality and greenhouse gas and carbon emissions aimed at protecting human health, mitigating climate change, and understanding the carbon cycle

Arctic fires re-emerging

Underground smouldering fires resurfaced early in 2020, contributing to the unprecedented wildfires that tore through the Arctic this spring and summer. An international effort is needed to manage a changing fire regime in the vulnerable Arctic

Sensitivity of atmospheric aerosol scavenging to precipitation intensity and frequency in the context of global climate change

Wet deposition driven by precipitation is an important sink for atmospheric aerosols and soluble gases. We investigate the sensitivity of atmospheric aerosol lifetimes to precipitation intensity and frequency in the context of global climate change. Our sensitivity model simulations, through some simplified perturbations to precipitation in the GEOS-Chem model, show that the removal efficiency and hence the atmospheric lifetime of aerosols have significantly higher sensitivities to precipitation frequencies than to precipitation intensities, indicating that the same amount of precipitation may lead to different removal efficiencies of atmospheric aerosols. Combining the long-term trends of precipitation patterns for various regions with the sensitivities of atmospheric aerosol lifetimes to various precipitation characteristics allows us to examine the potential impacts of precipitation changes on atmospheric aerosols. Analyses based on an observational dataset show that precipitation frequencies in some regions have decreased in the past 14 years, which might increase the atmospheric aerosol lifetimes in those regions. Similar analyses based on multiple reanalysis meteorological datasets indicate that the changes of precipitation intensity and frequency over the past 30 years can lead to perturbations in the atmospheric aerosol lifetimes by 10% or higher at the regional scale

Clinical Preceptors\u27 Perspectives on Clinical Education in Post-Professional Athletic Training Education Programs

Context: Clinical education is the interaction between a clinical preceptor and student within the clinical setting to help the student progress as a clinician. Post-professional athletic training clinical education is especially important to improve these students\u27 clinical knowledge and skills. However, little research has been conducted to assess the pedagogical principles for clinical education at this level or what factors are necessary to enhance the clinical skills and decision-making abilities of post-professional students. Therefore, exploring the perspectives of clinical preceptors involved in post-professional education will help educators understand what strategies are necessary to improve post-professional athletic training education programs (PPATEPs). Objective: To qualitatively investigate clinical preceptors\u27 perspectives and experiences regarding clinical education within PPATEPs. Design: Consensual qualitative research (CQR) with an emergent design. Setting: Telephone interviews were conducted with all participants. Patients or Other Participants: Eleven collegiate post-professional clinical preceptors (7 males, 4 females; average age = 38±7.3 years; average years as an athletic trainer = 15±6.6 years) who were affiliated with a PPATEP were interviewed, representing 11 out of 16 PPATEPs. Data Collection and Analysis: Interview transcripts were coded for themes and categories. Triangulation included a consensus process by the research team and member checking to verify the data. Results: Data analysis yielded four themes relating to clinical education in PPATEPs: importance of clinical education, clinical preceptor responsibilities, clinical preceptor qualities, and barriers to clinical education. Participants indicated that clinical education was important for students to develop clinical skills and give them opportunities to make patient care decisions, and that several fundamental responsibilities and qualities contribute to being an effective clinical preceptor at the post-professional level. Conclusions: Post-professional clinical preceptors recognized that an appropriate balance between autonomy and guided practice in clinical experiences fostered an effective learning environment which allowed post-professional students to improve their clinical and decision-making skills beyond their entry-level skill set. Preceptors should also demonstrate attributes of a clinician, educator, and communicator to be an effective mentor

Fusion approach for remotely sensed mapping of agriculture (FARMA):A scalable open source method for land cover monitoring using data fusion

The increasing availability of very-high resolution (VHR; &lt;2 m) imagery has the potential to enable agricultural monitoring at increased resolution and cadence, particularly when used in combination with widely available moderate-resolution imagery. However, scaling limitations exist at the regional level due to big data volumes and processing constraints. Here, we demonstrate the Fusion Approach for Remotely Sensed Mapping of Agriculture (FARMA), using a suite of open source software capable of efficiently characterizing time-series field-scale statistics across large geographical areas at VHR resolution. We provide distinct implementation examples in Vietnam and Senegal to demonstrate the approach using WorldView VHR optical, Sentinel-1 Synthetic Aperture Radar, and Sentinel-2 and Sentinel-3 optical imagery. This distributed software is open source and entirely scalable, enabling large area mapping even with modest computing power. FARMA provides the ability to extract and monitor sub-hectare fields with multisensor raster signals, which previously could only be achieved at scale with large computational resources. Implementing FARMA could enhance predictive yield models by delineating boundaries and tracking productivity of smallholder fields, enabling more precise food security observations in low and lower-middle income countries.</p

Low cost infrared and near infrared sensors for UAVs

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter

Patients Reasons for Choosing Office-based Buprenorphine: Preference for Patient-Centered Care

Objectives - To explore HIV-infected patients\u27 attitudes about buprenorphine treatment in office-based and opioid treatment program (OTP) settings. Methods - We conducted in-depth qualitative interviews with 29 patients with co-existing HIV infection and opioid dependence seeking buprenorphine maintenance therapy in office-based and OTP settings. We used thematic analysis of transcribed audiorecorded interviews to identify themes. Results - Patients voiced a strong preference for office-based treatment. Four themes emerged to explain this preference. First, patients perceived the greater convenience of office-based treatment as improving their ability to address HIV and other healthcare issues. Second, they perceived a strong patient-focused orientation in patient-provider relationships underpinning their preference for office-based care. This was manifest as increased trust, listening, empathy, and respect from office-based staff and providers. Third, they perceived shared power and responsibility in officebased settings. Finally, patients viewed office-based treatment as a more supportive environment for sobriety and relapse prevention. This was partly due to strong therapeutic alliances with office-based staff and providers who prioritized a harm reduction approach, but also due to the perception that the office-based settings were safer for sobriety, compared with increased opportunities for purchasing and using illicit opiates in OTP settings. Conclusions - HIV-infected patients with opioid dependence preferred office-based buprenorphine because they perceived it as offering a more patient-centered approach to care compared with OTP referral. Office-based buprenorphine may facilitate engagement in care for patients with co-existing opioid dependence and HIV infection

Remote sensing estimates of stand-replacement fires in Russia, 2002–2011

The presented study quantifies the proportion of stand-replacement fires in Russian forests through the integrated analysis of Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) data products. We employed 30 m Landsat Enhanced Thematic Mapper Plus derived tree canopy cover and decadal (2001–2012) forest cover loss (Hansen et al 2013 High-resolution global maps of 21st-century forest cover change Science 342 850–53) to identify forest extent and disturbance. These data were overlaid with 1 km MODIS active fire (earthdata.nasa.gov/data/near-real-time-data/firms) and 500 m regional burned area data (Loboda et al 2007 Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data Remote Sens. Environ. 109 429–42 and Loboda et al 2011 Mapping burned area in Alaska using MODIS data: a data limitations-driven modification to the regional burned area algorithm Int. J. Wildl. Fire 20 487–96) to differentiate stand-replacement disturbances due to fire versus other causes. Total stand replacement forest fire area within the Russian Federation from 2002 to 2011 was estimated to be 17.6 million ha (Mha). The smallest stand-replacement fire loss occurred in 2004 (0.4 Mha) and the largest annual loss in 2003 (3.3 Mha). Of total burned area within forests, 33.6% resulted in stand-replacement. Light conifer stands comprised 65% of all non-stand-replacement and 79% of all stand-replacement fire in Russia. Stand-replacement area for the study period is estimated to be two times higher than the reported logging area. Results of this analysis can be used with historical fire regime estimations to develop effective fire management policy, increase accuracy of carbon calculations, and improve fire behavior and climate change modeling efforts

Using the Landsat data archive to assess long-term regional forest dynamics assessment in Eastern Europe, 1985-2012

Abstract. Dramatic political and economic changes in Eastern European countries following the dissolution of the “Eastern Bloc” and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers