EEFlux: A Landsat-based Evapotranspiration mapping tool on the Google Earth Engine

“EEFlux” is an acronym for ‘Earth Engine Evapotranspiration Flux.’ EEFlux is based on the operational surface energy balance model “METRIC” (Mapping ET at high Resolution with Internalized Calibration), and is a Landsat-imagebased process. Landsat imagery supports the production of ET maps at resolutions of 30 m, which is the scale of many human-impacted and human-interest activities including agricultural fields, forest clearcuts and vegetation systems along streams. ET over extended time periods provides valuable information regarding impacts of water consumption on Earth resources and on humans. EEFlux uses North American Land Data Assimilation System hourly gridded weather data collection for energy balance calibration and time integration of ET. Reference ET is calculated using the ASCE (2005) Penman-Monteith and GridMET weather data sets. The Statsgo soil data base of the USDA provides soil type information. EEFlux will be freely available to the public and includes a web-based operating console. This work has been supported by Google, Inc. and is possible due to the free Landsat image access afforded by the USGS

Lifting the Information Barriers to Address Sustainability Challenges with Data from Physical Geography and Earth Observation

Sustainability challenges demand solutions, and the pace of technological and scientific advances in physical geography and Earth observation have great potential to provide the information needed to address these challenges. This paper highlights five online tools and initiatives that are lifting barriers to address these challenges. The enviroGRIDS project in the Black Sea catchment demonstrates how the use of spatial data infrastructures can facilitate data sharing. Google Earth Engine is providing solutions to challenges of processing big data into usable information. Additionally, application programming interfaces allow outsiders to elaborate and iterate on programs to explore novel uses of data and models, as seen in the Berkeley Ecoinformatics Engine. Finally, collaborative mapping tools, such as Seasketch/MarineMap and the InVEST software suite, allow engagement within and between groups of experts and stakeholders for the development, deployment, and long-term impact of a project. Merging these different experiences can set a new standard for online information tools supporting sustainable development from evidence brought by physical geography combined with socioeconomic conditions

Effect of body mass index on operative outcome after robotic-assisted Ivor-Lewis esophagectomy: retrospective analysis of 129 cases at a single high-volume tertiary care center.

The impact of body weight on outcomes after robotic-assisted esophageal surgery for cancer has not been studied. We examined the short-term operative outcomes in patients according to their body mass index following robotic-assisted Ivor-Lewis esophagectomy at a high-volume tertiary-care referral cancer center and evaluated the safety of robotic surgery in patients with an elevated body mass index. A retrospective review of all patients who underwent robotic-assisted Ivor-Lewis esophagectomy between April 2010 and June 2013 for pathologically confirmed distal esophageal cancer was conducted. Patient demographics, clinicopathologic data, and operative outcomes were collected. We stratified body mass index at admission for surgery according to World Health Organization criteria; normal range is defined as a body mass index range of 18.5-24.9 kg/m2. Overweight is defined as a body mass index range of 25.0-29.9 kg/m2 and obesity is defined as a body mass index of 30 kg/m2 and above. Statistics were calculated using Pearson\u27s Chi-square and Pearson\u27s correlation coefficient tests with a P-value of 0.05 or less for significance. One hundred and twenty-nine patients (103 men, 26 women) with median age of 67 (30-84) years were included. The majority of patients, 76% (N = 98) received neoadjuvant therapy. When stratified by body mass index, 28 (22%) were normal weight, 56 (43%) were overweight, and 45 (35%) were obese. All patients had R0 resection. Median operating room time was 407 (239-694) minutes. When stratified by body mass index, medians of operating room time across the normal weight, overweight and obese groups were 387 (254-660) minutes, 395 (310-645) minutes and 445 (239-694), respectively. Median estimated blood loss (EBL) was 150 (25-600) cc. When stratified by body mass index, medians of EBL across the normal weight, overweight and obese groups were 100 (50-500) cc, 150 (25-600) cc and 150 (25-600), respectively. Obesity significantly correlated with longer operating room time (P = 0.05) but without significant increased EBL (P = 0.348). Among the three body mass index groups there was no difference in postoperative complications including thrombotic events (pulmonary embolism and deep venous thrombosis) (P = 0.266), pneumonia (P = 0.189), anastomotic leak (P = 0.090), wound infection (P = 0.390), any cardiac events (P = 0.793) or 30 days mortality (P = 0.414). Our data study demonstrates that patients with esophageal cancer and an elevated body mass index undergoing robotic-assisted Ivor-Lewis esophagectomy have increased operative times but no significantly increased EBL during the procedure. Other potential morbidities did not differ with the robotic approach