Colwell, R. NNASA (non Center Specific)Colwell, Robert N. 1970 Applications of Remote Sensing In Agriculture and Forestry. In Ren-ota Sensing with Special Reference to Agriculture and Forestry. National Academy of Sciences. Washington, D.C....
Applications of Remote Sensing in Agriculture and Forestry Among the uses discussed in more detail than in Chapter 1 are: determining crop vigour and the agent responsible for any loss in crop vigour, estimating cr... HN Colwell,D Carneggie,R Croxton,... 被引量: 14发表: 1970年 Importance ...
For more than three decades, remote sensing has been envisioned as a useful source of data for inventorying and monitoring the Earth's surface for many purposes. One can apply the use of remote sensing to disciplines in agriculture, hydrology, forestry, oceanography, weather, land use, environ...
Human remote sensing with HAWKEYE glasses for early forest and agriculture stress detection 来自 Semantic Scholar 喜欢 0 阅读量: 33 作者:B Huberty,R Brock,CH Blazquez,V Ambrosia 摘要: Early detection of plant stress has always been a priority in forestry and agriculture. Identifying and treating...
Critical needs for remote sensing in agriculture are to provide spatial resolutions of 5–20 m, frequent coverage of 2–5 days, and rapid data delivery to the user. Aircraft platforms help in rectifying some of the problems associated with satellite acquisition in that spatial resolution can be ...
There are several types of sensors that are commonly used in UAV remote-sensing applications in the agricultural and forestry sectors. They can mainly be classified as follows: Optical RGB cameras:RGB sensors are the most widely used sensors on UAV systems for smart agriculture. They can take hi...
remote sensing in forestrycluster analysisMahalanobis distanceinductive methodsA rationale for using inductive methodology in remote sensing applied to monitoring of forest resources is given. The approach is tested using a Landsat TM scene of a part of eastern Norway. The image is classified using ...
The emphasis of the journal is on biophysical and quantitative approaches to remote sensing at local to global scales. Areas of interest include, but are not necessarily restricted to: Agriculture, forestry and range; Biophysical-spectral models; Ecology; Geography and land information; Geology and ...
and spectral resolution sensors in orbit in the near future will increase the utility of hyperspectral data in several research domains and will likely increase the number of users of HSI for soils, forestry, agriculture, urban, andcryosphereresearch. This chapter is intended as a resource to be...
Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote ...