32 results about "Vegetation remote sensing" patented technology

The invention provides a crop planting pattern classification method and system considering phenological characteristics, and relates to the field of vegetation remote sensing. By making full use of the difference of EVI time series curves in key phenological periods in the identification of planting pattern types, and by enhancing the weight of key phenological periods, the information of key phenological periods can be effectively used, and the information of non-critical phenological periods can be suppressed to improve the quality of crops. Accuracy of planting pattern classification.

The invention discloses a method for obtaining spatial distribution of desert riparian forests based on GIS buffer analysis, and belongs to the technical field of vegetation remote sensing monitoring in arid regions. It includes the following steps: Step 1: Download the TM remote sensing image of the river in the arid area, perform image preprocessing, remote sensing interpretation, and NDVI calculation on it, and obtain the NDVI remote sensing data of the desert riparian forest; Step 2: Extract the river bank boundary vector line, and remote sensing The images are uniformly registered and corrected under the GIS platform; Step 3: Generate multiple buffer vector maps around the river according to the research requirements; Step 4: Overlay the multiple buffer vector maps with the NDVI remote sensing data of the desert riparian forest, and extract each The mean value of NDVI in the buffer zone, with the vertical channel distance as the independent variable and the mean NDVI as the dependent variable, was used to analyze the horizontal spatial distribution structure of desert riparian forest by curve fitting. The invention provides a beneficial reference for determining the spatial continuous gradient distribution of the desert riparian forest and its protection range.

The invention provides a method of utilizing a multi-angle observation system to obtain the vegetation canopy spectroscopic data to precisely inverting sunlight induced chlorophyll fluorescence of shade / sun leaves of a canopy, and belongs to the research field of vegetation remote sensing inversion parameter obtaining methods. The method comprises following steps: establishing a multi-angle super-hyperspectral observing system; obtaining multi-angle super-hyperspectral data; calculating the solar incident angle and canopy reflection brightness; calculating the reflection rate and inverted chlorophyll fluorescence; using a leaf clamp to observe the leaf reflection rate; utilizing the ratio of canopy reflection rate to leaf reflection rate, under the assistance of a geometrical optical model, calculating the ratio of shade / sun leaves from different observation angles, and obtaining the fluorescence of the sun leaves and shade leaves through fitting of least square method. The provided method can obtain continuous multi-angle vegetation canopy super-hyperspectral data, is used to invert chlorophyll fluorescence, can simply and effectively calculate the ratio of sun leaves and shade leaves of a canopy from different observation angles and solar incident angles based on the leaf reflection rate and a geometrical optical model, calculates the fluorescence of the sun leaves and shadeleaves, and improves the precision of monitoring the primary productivity of a land.