Wildfires, Droughts, Forests and Satellites

  Drought and wildfires always seem to go together! The recent drought in California was accompanied by powerful fires that burnt several million acres of forest, including in the iconic Yosemite National Park.   The question that people often ask whenever there’s news of yet another fire resulting in severe damage to the forests is always –   isn’t there a way to figure out which areas of the forest are most vulnerable to the fires?   And until recently, most rangers and naturalists were estimating that vulnerability based on their experience and years of working in the same forest ecosystem.   Scientists from the University of California, Davis   studied aerial imagery from the forests  in California between the years 2012-2015 to predict the areas where most of the trees were dying, either due to a fire or after a fire had struck. What they found was that the areas that were the worst affected with the highest tree mortality were areas that were both dry and dense. From a commonsens

Snippets in Clean Technology and Data Science: Climate

  Data science has been used extensively in building climate models, downscaling climate models to regions, monitoring and evaluating the accuracy of climate models through  paleoclimate data as well as developing methods to mitigate the effects of climate change and develop alternative markets. Today’s post will look at some of the more straightforward uses of data, machine learning and spatial statistics in monitoring carbon emissions as well as building alternative market systems. The first of course is   monitoring and measuring carbon emissions   and emissions of other gases that contribute to the changing climate. Our first example comes from Europe. Researchers in Europe    created a tool to map the 177 regions in 27 countries of the EU and the carbon footprint associated with them. They used a database (EXIOBASE 2.3 multiregional input-output database) with detailed information about the world economy in 2007 and built a model that looked at the different factors impacting carb

Cooling The City – Green Facades For Mitigating Urban Heat

Anyone who’s ever visited an Indian city in the heat of summer will remember the feeling that the city itself is baking – heat radiates from the pavements, the buildings and there are fewer green areas to mitigate these effects. This is the urban heat island effect – when the city is much hotter than the surrounding areas. Urban heat islands are a common problem and are only going to get worse as the climate warms. This is especially true in countries closer to the equator – summer is hot but is now promising to get even hotter. One of the solutions that people have been looking at is “greening building facades” or more simply – growing plants along the walls of buildings – vertical greening. The advantages of “green building facades” are that the plants help reduce building temperatures through shading by the leaves, reducing the impact of wind and through evapotranspiration. Now, like any other natural system – growing plants vertically means that there are a number of parameters tha

Snippets in Clean Technology and Data Science: Sustainability Accounting

  Let’s take a look at one of the traditional clean tech sectors –   sustainability accounting . Now, this is a term that’s used in many different contexts, but traditionally, it refers to the use and flow of materials and energy. This could be locally, within a company, regionally for a specific sector across countries or monitoring a specific material over the globe. Most large companies these days track their   metrics on sustainability   –   carbon footprint, water usage, waste, conflict minerals   and so on… These metrics and the associated analyses are typically presented in reports that are one-time downloads or available in obscure places on the web. So anyone who’s interested in tracking changes over space and time for a single company or a group of companies – congratulations! You just agreed to spend a huge amount of time trying to get the data before doing anything with it. Enter the company   ESG Trends . This company was started a few years ago and has made it easier to f

Concurrent Air Pollution And Heat Waves Make People Sick

Fact – fifteen of the hottest years have come in the last sixteen years. If you are one of the people who is living through the heat waves and wondering if your asthma is really getting worse or if it’s just your imagination – well congratulations! You’re not alone and you are not imagining things. Scientists at the   University of California, Irvine    wanted to understand what happens to the air pollutants that trigger human health problems like asthma when heat waves occur simultaneously. In other words, if there is already air pollution does having a heat wave at the same time make the pollution worse? And if it does get worse, how badly does it affect people’s health?   In order to answer these questions, they overlaid detailed air pollution maps of the United States and Canada with meterological models and data about heat waves over a 15 year time period. The data was on a very fine 1 degree grid. What they found was that having both a heat wave and existing pollution resulted in

Snippets in Clean Technology and Data Science: Water

  Today, let’s look at some of the ways in which sensors, machine learning and other data science tools are helping solve problems in the water sector Water conservation   is one of the largest components of the water sector. And with the droughts hitting California, New South Wales and South Africa recently, there’s been a lot of focus on education and changing people’s behavior through information.  So how do we make it easy for people to do their best to minimize water use?   Companies and organizations have tried several different approaches – public education programs about water use being one such example. Another being the water comparison report that water companies in California started sending out to their customers with the monthly bill. It’s a short summary that shows how your water usage compares with your neighbors and how much water you have used against your allocation. This is a fairly straightforward use of data science – it uses a nearest neighbor approach with a bui

Snippets in Clean Technology and Data Science: Agriculture and Food

  In today’s post, we’ll take a look at a few problems in Agriculture and Food that are being solved using machine learning, computer vision, social networks and satellite data among other data science tools. What do social networks, sensors, food and farms have in common? Social media immediately makes us think about Facebook, Snapchat, Instagram, Whatsapp, Google and all the different ways in which we human beings connect with each other today. All these apps use Graph and Network Theory to understand how people may be connected to each other, the links between them and how strong or weak those connections are. Reid Hoffman of LinkedIn famously said that “we’re all six weak connections apart from each other” and in today’s connected world, that number looks like it’s getting smaller and smaller. So what would social media have in common with agriculture? First, there’s always the way in which farmers and workers interact and connect with each other.   Several startups like the Farmer