Remote Sensing (RS-Remote Sensing)—a modern science and technology that collects the electromagnetic wave information of the target object without contacting the object itself. . In other words, it is "remote perception", which is divided according to the sensor platform, including aerospace remote sensing, aerial remote sensing, and ground remote sensing.
As a means of aerial remote sensing, unmanned aerial vehicle remote sensing (UAVRS) technology has the advantages of long battery life, real-time image transmission, detection of high-risk areas, low cost, high resolution, and flexible maneuvering. It is a powerful supplement to satellite remote sensing and manned aerial remote sensing. It has been widely used abroad. It uses a high-resolution CCD camera system to obtain remote sensing images, uses air and ground control systems to realize automatic shooting and acquisition of images, and at the same time realizes flight path planning and monitoring, information data compression and automatic transmission, image preprocessing and other functions, which can be widely used Applied to national ecological environment protection, mineral resources exploration, marine environment monitoring, land use investigation, water resources development, crop growth monitoring and yield estimation, agricultural operations, natural disaster monitoring and evaluation, urban planning and municipal management, forest pest protection and monitoring, Public security, national defense, digital earth and other fields
1. Literature analysis, sensor selection, observation methods and quality control points of near-ground UAV vegetation remote sensing literature in the past ten years
1.1. Literature analysis of UAV vegetation remote sensing in the past ten years
Use of document analysis software VOSviewer (practice)
Key Research Directions, Research Institutions, and Scientists of UAV Vegetation Remote Sensing
1.2. The characteristics of UAV remote sensing and the difference with satellite remote sensing
Core advantages and four basic characteristics
Differences in imaging methods between UAV and satellite remote sensing images
1.3. UAV sensor types, characteristics and selection
Brief imaging geometry and spectral characteristics of consumer RGB cameras
Multispectral camera imaging types and core issues (band image registration, filters)
Hyperspectral Camera Imaging Mode and Spectral Authenticity
Thermal Infrared Camera Characteristics and Temperature Measurement Reliability
1.4. UAV remote sensing observation methods, characteristics and quality control
Nadir observation, multi-scale observation and oblique observation
Four typical multi-angle observation modes
Key Points of Image Quality Control
2. Radiation measurement and reflection characteristics of ground objects
2.1. Basic radiation metrics and surface radiation characteristics
Basic radiometric measurements from shallow to deep: radiant flux, irradiance, radiant intensity, radiance (derivation)
Lambert's cosine law and inverse square law of basic radiation laws (derivation)
Lambertian Surface Radiation and Radiation Anisotropy
2.2. Bidirectional reflection characteristics and representation of ground objects
Definition of Energy Conservation and Reflectivity (Derivation)
Detailed Explanation of BRDF and BRF of Dichroic Reflection on Non-Lambertian Surfaces (Derivation)
Nine reflection factors/rates (derived)
2.3. Spectral reflection characteristics and physical and physiological mechanisms of typical ground objects
Leaf Spectral Reflectance and Physical Physiological Mechanisms under Healthy and Stress Conditions
Characteristics and physical interpretation of soil spectral reflectance in various soil types and states
Basic ideas, principles and methods of vegetation index construction (example)
3. Radiation and geometric processing of UAV remote sensing images
3.1. Radiation processing of remote sensing images
Introduction of dark current, vignetting effect and atmospheric effect in imaging optical path
Two-way reflectivity acquisition method of imaging sensor radiometric calibration (practice + code explanation)
Absolute and Relative Calibration
3.2. Geometric correction of remote sensing images
Brief Principles of Imaging Geometry and Projective Transformation
Imaging Distortion and Correction Method
Generation of orthophoto, DEM, DSM (practice + code explanation)
3.3. Photogrammetric SfM point cloud
Projection and backprojection of 2D images and 3D point clouds (practice + code explanation)
Image and SfM point cloud joint use case (practice)
Point cloud denoising, filtering, normalization, canopy height model production, single tree detection and segmentation (practice)
4. Radiation transfer mechanism of light in vegetation leaves and canopy and application of plane model
4.1. Introduction to the structure and function of vegetation
Structure and function at the leaf scale
Structure and function at the plant/canopy scale
Detailed definition of canopy coverage and leaf area index
4.2. Broad leaf radiative transfer model
Monocot plate model PLATE (derivation)
Dicotyledon multi-layer plate model PROSPECT (detailed code)
4.3. Beer-Lambert Law and Leaf Area Index
Beer-Lambert Law and Gap Rate Theory (Two Derivations)
Projection G function and aggregation index (derivation + code)
4.4. One-dimensional radiative transfer model of canopy
Detailed explanation of SAIL model
5. Remote sensing estimation of vegetation coverage and leaf area index
5.1. Estimation of vegetation coverage from UAV images
Traditional Image Segmentation and Pixel Decomposition
Forest Canopy Cover Estimation
5.2. Estimation of LAI from UAV images
Inversion Based on Gap Ratio Model
Inversion Based on SAIL Model
Inversion based on machine learning models
Original article: Practical technology application of near-ground UAV vegetation quantitative remote sensing and physiological parameter inversion
