RESUMEN
Urban agriculture can contribute to sustainable development. However, a holistic investigation is lacking to comprehend its positive and negative impacts on the Sustainable Development Goals (SDGs). Our systematic analysis of around 1,450 relevant publications on urban agriculture, screened from 76,000 records, fills this gap. We map and analyze the text in the literature for each SDG target and its associated positive or negative sentiments. Here, we report our results highlighting that urban agriculture is linked to all SDGs, with 142 and 136 targets having positive and negative sentiments. The mapped positive sentiments are around double the negative ones. We identify six leveraging opportunities urban agriculture provides for sustainable transformation with four hurdles to be resolved. Urban agriculture does not inherently contribute to sustainability. Its impacts rely on the adoption of specific practices. Realizing urban agriculture's social, economic, and environmental functions to accelerate SDG progress requires tackling the hurdles.
RESUMEN
Rainfall-induced landslides cause frequent disruptions to critical infrastructure in mountainous countries. Climate change is altering rainfall patterns and localizing extreme rainfall events, increasing the occurrence of landslides. For planning climate-resilient critical infrastructure in landslide-prone regions, it is urgent to understand the changing landslide susceptibility in relation to changing rainfall extremes and spatially overlay them with critical infrastructure to determine risk zones. As such, areas requiring financial reinforcements can be prioritized. In this paper, we develop a framework linking changing rainfall extremes to landslide susceptibility and intensity of critical infrastructure - exemplified on a national scale using Nepal as a case study. First, we define a set of 21 different unique rainfall indices that describe extreme and localized rainfall. Second, we prepare a new annual (2016-2020) inventory of 107,900 landslides in Nepal mapped on PlanetScope satellite imagery. Next, we prepare a landslide susceptibility map by training a random forest model using the collected extreme rainfall indices and landslide locations in combination with spatial data on topography. Fourth, we construct a gridded critical infrastructure spatial density map that quantifies the intensity of infrastructure (i.e., transportation, energy, telecommunication, waste, water, health, and education) at each grid location using OpenStreetMap. The landslide susceptibility map classified Nepal's topography into low (36 %), medium (33 %), and (32 %) high rainfall-triggered landslide susceptibility zones. The landslide susceptibility map had an average area under the receiver characteristic curve value of 0.94. Finally, we overlay the landslide susceptibility map with the critical infrastructure intensity to identify areas needing financial reinforcement. Our framework reasonably mapped critical infrastructure hotspots in Nepal prone to landslides on a 1 km grid. The hotspots are mainly concentrated along major national highways and in provinces 4, 3, and 1, highlighting the need for improved land management practices. These hotspots need spatial prioritization regarding climate-resilient critical infrastructure financing and slope conservation policies. The research data, output maps, and code are publicly released via an ArcGIS WebApp and GitHub repository. The framework is scalable and can be used for developing infrastructure financing strategies for landslide mountain regions and countries.
