Vol. 10 No. 2 (2021)

Open Access

Article

Article ID: 500

Integrating Optical and Microwave Satellite Observations for High Resolution Soil Moisture Estimate and Applications in CONUS Drought Analyses

by Donglian Sun, Yu Li, Xiwu Zhan, Chaowei Yang, Ruixin Yang

Remote Sensing, Vol.10, No.2, 2019; 404 Views, 26 PDF Downloads

In this study, optical and microwave satellite observations are integrated to estimate soil moisture at high spatial resolution and applied for drought analysis in the continental United States.  To estimate soil moisture, a new refined model is proposed to estimate soil moisture (SM) with auxiliary data like soil texture, topography, surface types, accumulated precipitation, in addition to Normalized Difference Vegetation Index and Land Surface Temperature (LST) used in the traditional universal triangle method. It is found the new proposed SM model using accumulated precipitation demonstrated close agreements with the U.S. Drought Monitor (USDM) spatial patterns.  Currently, the USDM is providing a weekly map.  Recently, “flash” drought concept appears. To obtain drought map on daily basis, LST is derived from microwave observations and downscaled to the same resolution as the thermal infrared LST product and used to fill the gaps due to clouds in optical LST data. With the integrated daily LST available under nearly all weather conditions, daily soil moisture can be estimated at relatively high spatial resolution, thus drought maps based on soil moisture anomalies can be obtained at high spatial resolution on daily basis and made the flash drought analysis and monitoring become possible.

Open Access

Article

Article ID: 283

Crop indentification based on hyperspectral remote sensing

by tian Shu tian Shu

Remote Sensing, Vol.10, No.2, 2021; 172 Views, 14 PDF Downloads

I hyperspectral Remote Sensing provides a new technical means for the identification of crop species<b 12>, which isof significance for thedevelopment of precision agriculture. In this study, spectral characteristics-based identification were conducted on 7 crops at harvest by using different data Forms and commonly used vegetation indices. The reflectivity of Canna is very prominent in 350-500 nm wavelength, and The spectral reflectance of crops varied in 760-915 nm,1 000-1/Nm. The best wavelengths for identification of the 7 crops is 516 nm, 568 nm, 609 nm, 642nm, </b 18>660 nm,nm, 717 nm , 760 nm , 928 nm , 1 001 nm , 1 118 nm , 1 136 nm and 1 327 nm. Among vegetation indices, rv/ showed the strongest identifying potential followed by Msri b129>,NV/, tdv/ , ev/ , ndv/ , sav/ , DV /, tv/ , /pv/.To sum up , The characteristic spectrum and vegetation index are capable of crop discrimination.

Open Access

Article

Article ID: 277

Block-adjustment algorithm and Test for Three-line-array Image of high-resolution Remote sensing satellite

by Chubin Liu Liu, Yongsheng Zhang, Dazhao Fan, Rong Lei

Remote Sensing, Vol.10, No.2, 2021; 196 Views, 14 PDF Downloads

The geometric positioning process of high-resolution remote sensing satellite images was outlined. The necessity of block adjustment was analyzed. Combined with the imaging characteristics of line sensors, rigorous geometric model, satellite orbit model and interior O Rientation error model were researched on. Then The block math model of high-esolution remote Sensing satellite image was constructed. The elements of exterior orientation and interior orientation were using block solved method. ZY03 satellite images and ALOS PRISM images were tested in this way. The experiment demonstrated that the block adjustment method could improve the geometric accuracy of high-esolution E sensing satellite images