The increasing availability of high-frequency, high-resolution remotely sensed data promises a revolution in our understanding of land-use and land-cover change. We investigate how measures of forest biodiversity and carbon stocks can be derived from these remotely sensed data, how these workflows can be streamlined and how these elements can be made available to support in-country spatial planning and policy-making. This work has been undertaken as a contribution to the new SPACES (Spatial Intelligence for Climate and Nature) coalition, which aims to mobilize spatial intelligence to support governments, businesses, finance institutions, funders, and investors in implementing the climate and nature agendas.