There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

/pdf/remote-sensing-of-the-environment-4yfxjaaswe.pdf

Remote sensing of the environment

Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV) Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface In the real-world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed This paper reviews more than 100 VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas

/pdf/significant-remote-sensing-vegetation-indices-a-review-of-4szax6zlwz.pdf

Significant remote sensing vegetation indices: A review of developments and applications

[1] Arctic amplification (AA) – the observed enhanced warming in high northern latitudes relative to the northern hemisphere – is evident in lower-tropospheric temperatures and in 1000-to-500 hPa thicknesses. Daily fields of 500 hPa heights from the National Centers for Environmental Prediction Reanalysis are analyzed over N. America and the N. Atlantic to assess changes in north-south (Rossby) wave characteristics associated with AA and the relaxation of poleward thickness gradients. Two effects are identified that each contribute to a slower eastward progression of Rossby waves in the upper-level flow: 1) weakened zonal winds, and 2) increased wave amplitude. These effects are particularly evident in autumn and winter consistent with sea-ice loss, but are also apparent in summer, possibly related to earlier snow melt on high-latitude land. Slower progression of upper-level waves would cause associated weather patterns in mid-latitudes to be more persistent, which may lead to an increased probability of extreme weather events that result from prolonged conditions, such as drought, flooding, cold spells, and heat waves.

The collection 6 MODIS active fire detection algorithm and fire products.

Surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. Recent technological advances in satellite remote sensing have shown that soil moisture can be measured by a variety of remote sensing techniques, each with its own strengths and weaknesses. This paper presents a comprehensive review of the progress in remote sensing of soil moisture, with focus on technique approaches for soil moisture estimation from optical, thermal, passive microwave, and active microwave measurements. The physical principles and the status of current retrieval methods are summarized. Limitations existing in current soil moisture estimation algorithms and key issues that have to be addressed in the near future are also discussed.

/pdf/satellite-remote-sensing-applications-for-surface-soil-bewisw0hw4.pdf

Satellite remote sensing applications for surface soil moisture monitoring: A review

[1] A new index, the Normalized Multi-band Drought Index (NMDI), is proposed for monitoring soil and vegetation moisture from space. NMDI is defined as , where R represents the apparent reflectance observed by a satellite sensor. Similar to the Normalized Difference Water Index, NMDI uses the 860 nm channel as the reference; instead of using a single liquid water absorption channel, however, it uses the difference between two liquid water absorption channels centered at 1640 nm and 2130 nm as the soil and vegetation moisture sensitive band. Analysis revealed that by combining information from multiple near infrared, and short wave infrared channels, NMDI has enhanced the sensitivity to drought severity, and is well suited to estimate both soil and vegetation moisture. Typical soil reflectance spectra and satellite-acquired reflectances, are used to validate the usefulness of NMDI. Its application to areas with moderate vegetation coverage, however, needs further investigation.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007GL031021

NMDI: A normalized multi-band drought index for monitoring soil and vegetation moisture with satellite remote sensing

[1] Trends in Chinese horizontal visibility, the frequency of visibility >19 km, and haziness for the period between 1981 and 2005 were evaluated based on data for daily horizontal visibility. Annual means were calculated for each station and for China as a whole. Linear regression analysis was used to characterize long-term annual trends in these variables. Over the past 25 years, there has been a significant decrease in horizontal visibility (−2.1 km per decade from 1990 to 2005) and the frequency of visibility >19 km (−3.5% per decade) but a significant increase in the 75th percentile annual extinction coefficients (25% per 25 year). According to rapid increase of total energy consumption, the consistent spatial and temporal variations of visibility and haze support the speculation that increased aerosol loadings were responsible for the observed decreases in horizontal visibility over much of East China.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007GL031450

Horizontal visibility trends in China 1981–2005

This paper presents the patterns and trends of haze over 31 provincial capitals in China between 1980 and 2005. The haze measurements were based on human visual range observations at 31 synoptic meteorological stations operated by the China Meteorological Administration (CMA). The high haze regions were found in largely populated cities such as Chongqing, Beijing, and Shenyang, while the low haze regions were located in the cities with small populations such as Lhasa, Kunming, and Guiyang in southwestern China and Haikou in southern China. The haziness of the 12 cities shows a significantly (95%) decreasing trend, while that of the 13 cities shows a significantly increasing trend over the 25-year study period. The increases are evident in the eastern and southwestern cities in China. It has also been found that there is a decreasing haze trend in winter but an increasing trend in summer for many cities. Nonetheless, the causality for the reduction of aerosol emissions has not been established. This report is the first survey and preliminary analysis done on haze patterns and trends from 1980 to 2005 over the capital cities of 31 provinces in Mainland China.

Haze trends over the capital cities of 31 provinces in China, 1981–2005

Sand and dust storms (SDSs), which present environmental risks and affect the regional climate, have been worsened in the East Asian regions over the last decade. Monitoring SDS from space using satellite remote sensing (RS) has become one of the most important issues in this field. At present, satellite RS of SDS is limited to using true-color images or aerosol optical thickness (AOT), or a new algorithm called "Deep Blue". Using current existing approaches makes it difficult to identify SDS from clouds. The authors have detected SDS by combining Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) solar reflectance band (SRB) measurements. Based on the dust spectral characteristic, this letter proposes a normalized difference dust index (NDDI) using MODIS reflectance measurements and applies it to the Asian SDS cases. The simple NDDI index is found to be able to identify SDS and clouds easily. The results suggest that NDDI could be used to detect SDS over bright surfaces where the MODIS AOT product is not available

/pdf/asian-dust-storm-monitoring-combining-terra-and-aqua-modis-4g91x8rbg5.pdf

John J. Qu

Papers

Satellite remote sensing applications for surface soil moisture monitoring: A review

NMDI: A normalized multi-band drought index for monitoring soil and vegetation moisture with satellite remote sensing

Horizontal visibility trends in China 1981–2005

Haze trends over the capital cities of 31 provinces in China, 1981–2005

Asian Dust Storm Monitoring Combining Terra and Aqua MODIS SRB Measurements