<p>Land use / land cover (LULC) maps provide critical information to governments, land use planners, and decision-makers about the spatial layout of the environment and how it is changing.  While a variety of LULC products exist, they are often coarse in resolution, not updated regularly, or require manual editing to be useful.  In partnership, Esri, Microsoft Planetary Computer, and Impact Observatory created the world’s first publicly available 10-m LULC map by automating and sharing a deep-learning model that was run on over 450,000 Sentinel-2 scenes.  The resulting map, released freely on Esri’s Living Atlas in June 2021, displays ten classes across the globe: built area, trees, scrub/shrub, cropland, bare ground, flooded vegetation, water, grassland, permanent snow/ice, clouds.  Here, we discuss key findings from the resulting map, including a quantitative analysis of how 10-m resolution allows us to assess small, low density urban areas compared to other LULC products, including the Copernicus CGLS-LC100 100-m resolution global map.  We will also share how we support project-based, on-demand LULC mapping and will present preliminary findings from a new globally consistent 2017-2021 annual LULC dataset across the entire Sentinel-2 archive.</p>

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The goal of this work is to develop a new autonomous capability for remotely deploying precisely located sensor nodes without damaging the sensor nodes in the process. Over the course of the last decade there has been significant interest in research to deploy sensor networks. This research is driven by the fact that the costs associated with installing sensor networks can be very high. In order to rapidly deploy sensor networks consisting of large numbers of sensor nodes, alternative techniques must be developed to place the sensor nodes in the field. Figure 1 Prototype intelligent gas gun with magazine to hold 3 sensor packagesTo date much of the research on sensor network deployment has focused on strategies that involve the random dispersion of sensor nodes [1]. In addition other researchers have investigated deployment strategies utilizing small unmanned aerial helicopters for dropping sensor networks from the air.[2]. The problem with these strategies is that often sensor nodes need to be very precisely located for their measurements to be of any use. The reason for this could be that the sensor being used only have limited range, or need to be properly coupled to the environment which they are sensing. The problem with simply dropping sensor nodes is that for many applications it is necessary to deploy sensor nodes horizontally. In addition, to properly install many types of sensors, the sensor must assume a specific pose relative to the object being measured. Figure 2. Remote sensor placement package embedded in a piece of fiber board using the remote sensor placement deviceIn order to address these challenges we are currently developing a technology to remotely and rapidly deploy precisely located sensor nodes. The remote sensor placement device being developed can be described as an intelligent gas gun (Figure 1). A laser rangefinder is used to measure the distance to a specified target sensor location. This distance is then used to estimate the amount of energy required to propel the sensor node to the target location with just enough additional energy left over to ensure the sensor node is able to attach itself to the target of interest. We are currently in the process of developing attachment mechanisms for steel, wood, fiberglass ( Figure 2).In this demonstration we will perform a contained, live demo of our prototype pneumatic remote sensor placement device along with some prototype sensor attachment mechanisms we are developing.

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