Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Automatic Forest-Fire Measuring Using Ground Stations and Unmanned Aerial Systems
Forest Fire Modeling and Early Detection using Wireless Sensor Networks
LiDAR remote sensing of forest structure
Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle
Forecasting and visualization of wildfires in a 3D geographical information system
Using unmanned aerial vehicle for remote sensing application
Ground-Based 3D Radar Imaging of Trees Using a 2D Synthetic Aperture
Forest change detection from Sentinel-1 and ALOS-2 satellite images
Use of airborne LiDAR and aerial photography in the estimation of individual tree heights in forestry
Forest Fire Detection Algorithm Based on Digital Image
Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy
A data mining approach to predict forest fires using meteorological data
A Grassroots Remote Sensing Toolkit Using Live Coding, Smartphones, Kites and Lightweight Drones
Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland
Self-Autonomous Wireless Sensor Nodes With Wind Energy Harvesting for Remote Sensing of Wind-Driven Wildfire Spread
Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring
A cooperative UAV/UGV platform for wildfire detection and fighting
SINGLE TREE DETECTION IN FOREST AREAS WITH HIGH-DENSITY LIDAR DATA
Fusion of LiDAR and radar data for land-cover mapping in natural environments
Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy
Remote sensing and geographic information systems
Active Sense Queue Management (ASQM)
Precise Positioning of Pneumatic Artificial Muscle Systems
SILT: a memory-efficient, high-performance key-value store
FOREST FIRE RISK ZONE MAPPING FROM SATELLITE IMAGERY AND GIS A CASE STUDY
Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study