Remote sensing technology has brought the upgrade of agricultural drone technology

Remote sensing technology has brought the upgrade of agricultural drone technology

Since the emergence of civilian resource satellites in the 1970s, agriculture has become a field where remote sensing technology has been put into practical use and significant revenues. Especially with the emergence of high-space, hyperspectral and high-time-resolution remote sensing data, agricultural remote sensing technology has made breakthroughs in key technologies such as long-term sequence crop growth dynamic monitoring, crop species segmentation, and field fine agricultural information acquisition. Agricultural remote sensing monitoring mainly uses crops and soil as the object, and uses the spectral characteristics of the ground objects to be used for monitoring crop growth, crop quality, crop pests and diseases.

Because remote sensing technology has the characteristics of large coverage area and short revisit period, it is mainly applied to the investigation, evaluation, monitoring and management of large-scale agricultural production. Its application in agriculture is summarized into the following four categories:

1. Agricultural resources survey. Including the investigation of current resources such as cultivated land resources and soil resources, as well as dynamic monitoring of land desertification and salting, farmland environmental pollution, soil erosion, etc., providing the quantity, distribution and changes of various resources, as well as various resource evaluations based on surveys. Propose the countermeasures that should be taken for the organization, management and decision-making of agricultural production.

2. Estimated production of crops. It includes growth monitoring and yield forecasting of large crops such as wheat, corn, rice, and cotton, as well as grassland yield estimation and fruit tree growth monitoring.

3. Agricultural disaster forecasting. It includes dynamic monitoring of crop pests and diseases, freezing damage, floods and droughts, dry and hot winds, as well as damage investigation and assessment of farmland damage and crop yield reduction.

4. Agriculture. The main purpose is to use the high spatial resolution satellite data to investigate the current situation of farmland area and distribution, as well as the monitoring of farmland-scale crop growth, pests and soil moisture for farmland fertilization, application and irrigation.

5. The advantages of optical remote sensing and microwave remote sensing with different spatial resolutions are different for different applications. For example, high spatial resolution remote sensing data mainly uses field scale agriculture, while high time resolution wide coverage remote sensing data is mainly used for large area crop growth monitoring.

A new generation of agricultural drone technology application

Unmannedaerialvehicle (UAV) is a new remote sensing platform driven by power, unmanned and reusable on the aircraft. It has the characteristics of flexibility and real-time performance superior to other remote sensing platforms. Especially with the miniaturization of visible-near-infrared aeronautical imaging spectrometers and aerial CCD digital cameras, it is possible to obtain visible-near-infrared images with centimeter-level spatial resolution at any time, so the UAV remote sensing system is currently in environmental protection, agriculture, and disaster relief. The application field has been rapidly expanded.

Agricultural satellite remote sensing technology is affected by weather, orbital period, spatial resolution, etc. There are still many deficiencies in farmland monitoring at the field scale. It is often difficult to provide high-quality remote sensing data in time. UAV remote sensing can be combined with large-area satellite remote sensing. Cooperate with each other to form a multi-scale agricultural information monitoring network. UAV remote sensing can take advantage of fine-scale and dynamic continuous monitoring of farmland, applied to farmland plot boundary and area survey, crop species identification and statistics, crop growth analysis, crop nutrient and soil moisture monitoring, especially after agricultural disasters. In terms of assessment, UAV remote sensing technology will play a unique role.

Agricultural ground sensor network combined with remote sensing technology

At present, various types of ground-based observation technology and networking construction based on wired and wireless sensors are gradually developed and improved, which provides important authenticity information for satellite remote sensing surface surface inversion, model assimilation and coupling, and accuracy verification. In the agricultural field, the agricultural ground sensor network based on modern Internet of Things technology has been rapidly applied in intelligent greenhouse and field operation management. In particular, various types of sensors that automatically collect crop leaf surface to canopy, soil surface layer to section physical and chemical information, and environmental information such as temperature, humidity, and illumination of farmland are constantly appearing, plus wireless transmission network and intelligent control system, so that farmland information ground collection The convenience, sex and timeliness have been significantly improved.

Coupling of agricultural professional models with remote sensing technology

The advantage of remote sensing technology is that it provides a wide range of Earth observation data in multi-scale, multi-band and multi-reality, and can acquire surface feature information such as vegetation index, brightness index and surface radiation temperature in time, and further obtain it through quantitative inversion. Surface characteristic parameters such as surface reflectance, leaf area index, soil moisture content, and the like. However, agricultural remote sensing, especially crop remote sensing monitoring, the key attributes of crop height, leaf area and biomass are continuous dynamic changes during the growth period. It is difficult to ensure the continuity of observation by remote sensing data alone. Therefore, a large number of studies are to couple or assimilate various agricultural professional models such as crop growth models and surface energy balance models with remote sensing data to compensate for the shortcomings of remote sensing observation time resolution.

The new development trend is to improve the applicability of the traditional agricultural professional model. Overcoming the model is based on the farmland plot test as a sample, and less considering the shortcomings of the spatial heterogeneity of the object; the second is to take advantage of the multi-source data of the satellite, combined with the ground. The sensor network improves the periodicity of information collection; the third is to attach importance to the standardization and operation of remote sensing data products, such as MODIS series data products, which can provide 8d vegetation index, leaf area and other data products, making it easier for traditional agronomists to remotely sense. The data was introduced into various agricultural professional models.

(Original title: Application of Remote Sensing Technology in Agriculture)