We present planning challenges, methods and preliminary results for a new\nmodel-based paradigm for earth observing systems in adaptive remote sensing.\nOur heuristically guided constraint optimization planner produces coordinated\nplans for multiple satellites, each with multiple instruments (payloads). The\nsatellites are agile, meaning they can quickly maneuver to change viewing\nangles in response to rapidly changing phenomena. The planner operates in a\nclosed-loop context, updating the plan as it receives regular sensor data and\nupdated predictions. We describe the planner's search space and search\nprocedure, and present preliminary experiment results. Contributions include\ninitial identification of the planner's search space, constraints, heuristics,\nand performance metrics applied to a soil moisture monitoring scenario using\nspaceborne radars.\n