To　recognize　and　locate　fire　accurately,　we　developed　a　wildfire-locating　method　based　on　superpixel　features.　Previous　research　detected　fire　at　the　pixel　level　of　the　image　using　deep　learning,　whereas　we　preprocessed　and　classified　superpixels　for　fire　recognition　and　locating.　Firstly,　a　simple　linear　iterative　clustering　algorithm　was　created　to　segment　the　image　into　superpixel　blocks.　Then,　color,　texture,　and　shape　features　were　extracted　from　each　superpixel,　and　a　convolutional　neural　network　(CNN)　was　employed　to　classify　the　superpixels　into　two　categories:　fire　superpixels　and　background　superpixels.　Finally,　superpixels　were　refined　based　on　the　superpixel　adjacency　relationship.　Experimental　results　demonstrated　that　the　combined　approach　of　superpixel　features　and　CNNs　performed　satisfactory　segmentation　performance　with　an　accuracy　of　96.58%,　which　was　effective　in　wildfire-locating.　©　2024　IEEE.