Sustainability and climate monitoring efforts create a need for long-term remote sensing of  large geographic areas.  However, environmental monitoring in remote areas of developing countries remains impeded by a lack of low-cost, scalable IoT~solutions.  Whereas IoT systems for remote sensing abound,  they mostly are either low-cost or suitable for large areas, but not both. In this paper, we present a low-cost low-power network solution for remote sensing of areas up to hundreds of square kilometers.  Taking advantage of LoRa technology, we develop a self-organizing mesh network that can be scaled to a hundred and more nodes. Scalability is achieved by developing methods that mitigate packet collisions during data collection.  We present a protocol, called CottonCandy, with which nodes self-organize in a spanning-tree network topology in a distributed fashion. A power profile on a  custom-built circuit board shows that CottonCandy nodes can run  thousands of duty cycles on 2~AA batteries, sufficient to operate for years in many applications. Using off-the-shelf components, the cost of a CottonCandy node is less than US-$ 15.  Evaluations by simulation show that CottonCandy networks with 100 nodes achieve a packet delivery ratio of >90%. Measurements of an outdoor deployment with 15~nodes corroborate the high packet delivery ratio in a real-life setting.