The new level of precision and global coverage provided by satellite altimetry is rapidly advancing studies of ocean circulation. It allows for new insights into marine geodesy, ice sheet movements, plate tectonics, and for the first time provides high-resolution bathymetry for previously unmapped regions of our watery planet and crucial information on the large-scale ocean features on intra-season to interannual time scales. Satellite Altimetry and Earth Sciences has integrated the expertise of the leading international researchers to demonstrate the techniques, missions, and accuracy of satellite altimetry, including altimeter measurements, orbit determination, and ocean circulation models. Satellite altimetry is helping to advance studies of ocean circulation, tides, sea level, surface waves and allowing new insights into marine geodesy. Satellite Altimetry and Earth Sciences provides high resolution bathymetry for previously unmapped regions of our watery planet. Satellite Altimetry and Earth Sciences is for a very broad spectrum of academics, graduate students, and researchers in geophysics, oceanography, and the space and earth sciences. International agencies that fund satellite-based research will also appreciate the handy reference on the applications of satellite altimetry.

Satellite altimetry and Earth sciences :a handbook of techniques and applications

Estimating volumetric surface moisture content for cropped soils using a soil wetness index based on surface temperature and NDVI

Rice means life for millions of people and it is planted in many regions of the world. It primarily grows in the major river deltas of Asia and Southeast Asia, such as the Mekong Delta, known as the Rice Bowl of Vietnam, the second-largest rice-producing nation on Earth. However, Latin America, the USA, and Australia have extensive rice-growing regions. In addition, rice is the most rapidly growing source of food in Africa. Rice is therefore of significant importance to food security in an increasing number of low-income food-deficit countries. This review article gives a complementary overview of how remote sensing can support the assessment of paddy rice cultivation worldwide. This article presents and discusses methods for rice mapping and monitoring, differentiating between the results achievable using different sensors of various spectral characteristics and spatial resolution. The remote sensing of rice-growing areas can not only contribute to the precise mapping of rice areas and the assessment of the dynamics in rice-growing regions, but can also contribute to harvest prediction modelling, the analyses of plant diseases, the assessment of rice-based greenhouse gas methane emission due to vegetation submersion, the investigation of erosion-control-adapted agricultural systems, and the assessment of ecosystem services in rice-growing areas.

Remote sensing of rice crop areas

Precision agriculture is an emerging farm management strategy that is changing the way people farm. At present, there is an increasing commitment to reduce reliance on excessive chemical inputs in agriculture. Numerous technologies have been applied to make agricultural products safer and to lower their adverse impacts on the environment, a goal that is consistent with sustainable agriculture. Precision agriculture has emerged as a valuable component of the framework to achieve this goal. This review highlighted on remote sensing technology and describes how it can be used as an effective tool in precision agriculture.

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A Review: The Role of Remote Sensing in Precision Agriculture

Paddy rice agriculture plays an important role in various environmental issues including food security, water use, climate change, and disease transmission. However, regional and global paddy rice maps are surprisingly scarce and sporadic despite numerous efforts in paddy rice mapping algorithms and applications. With the increasing need for regional to global paddy rice maps, this paper reviewed the existing paddy rice mapping methods from the literatures ranging from the 1980s to 2015. In particular, we illustrated the evolution of these paddy rice mapping efforts, looking specifically at the future trajectory of paddy rice mapping methodologies. The biophysical features and growth phases of paddy rice were analyzed first, and feature selections for paddy rice mapping were analyzed from spectral, polarimetric, temporal, spatial, and textural aspects. We sorted out paddy rice mapping algorithms into four categories: (1) Reflectance data and image statistic-based approaches, (2) vegetation index (VI) data and enhanced image statistic-based approaches, (3) VI or RADAR backscatter-based temporal analysis approaches, and (4) phenology-based approaches through remote sensing recognition of key growth phases. The phenology-based approaches using unique features of paddy rice (e.g., transplanting) for mapping have been increasingly used in paddy rice mapping. Current applications of these phenology-based approaches generally use coarse resolution MODIS data, which involves mixed pixel issues in Asia where smallholders comprise the majority of paddy rice agriculture. The free release of Landsat archive data and the launch of Landsat 8 and Sentinel-2 are providing unprecedented opportunities to map paddy rice in fragmented landscapes with higher spatial resolution. Based on the literature review, we discussed a series of issues for large scale operational paddy rice mapping.

Evolution of regional to global paddy rice mapping methods: A review

Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop

Results from an approach to infer surface soil moisture from time series analysis of surface wetness index derived using the Special Sensor Microwave/Imager (SSM/I) are presented. Soil moisture quantification was based on the study of temporal changes in surface wetness index and its scaling to maximum and air‐dry limits of soil in each grid cell (0.33°). The estimated soil moisture of Illinois, USA was compared with field measured soil moisture (0–10 cm) obtained from the Global Soil Moisture Data Bank. A root mean square error of 7.18% was found between estimated and measured volumetric soil moisture. A consistency in soil moisture and rainfall pattern was found in the un‐irrigated areas of northern India (Jodhpur, Varanasi) and southern India (Madurai), influenced by southwest and northeast monsoons, respectively. Soil moisture of more than 0.30 m3m−3 was observed in the absence of rainfall due to the irrigation of rice crop in (Punjab) during the pre‐southwest monsoon period (May).

Spatial and temporal patterns of surface soil moisture over India estimated using surface wetness index from SSM/I microwave radiometer

The paper reports a unique observation from remote sensing records that the temporal rice growth pattern in terms of time of emergence and peak vegetation stage has been advanced by 3 –4 weeks in Punjab , In dia from 1981 to 2000. Analysis was carried out using multi -temporal remote sensing data from the optical sensors such as Advanced High Resolution Radiom eter (AVHRR) and the passive microwave sensors such as Special Sensor Microwave Imager (SSM/I) onboard NOAA and DMSP series of satellites respectively. The rice growth characteristics were quantified by Badhwar and Gaussian model fitting on seasonal Normalized Di fference Vegetation Index (NDVI) covering the mo n-soo n period (kharif season) for six years. The o b served time of peak vegetation stage of rice estimated from the average growth profile of years 1981–82 was 4 September, which advanced to 8 Au gust in years 1999 –2000. This change in phenology was further co n-firmed using Basist Wetness Index (BWI) da ta derived using multi frequency approach. The BWI data repr e-senting surface moisture/water fra ction were found to reach maximum in the middle of July in 1988, com-pared to middle of June in 1998. Temporal trends in mean BWI of Punjab during May –June also i nd icate a shift in crop growth profile and gradual in crease in area flooded with water for rice transplanting with time. Keywords: Crop, phenology, remote sensing, micro-wave. Q

Observing long-term changes in rice phenology using NOAA-AVHRR and DMSP-SSM/I satellite sensor measurements in Punjab, India

The widespread retreat of glaciers can be considered as a response to the climate change. Being the largest retreating glacier–ice shelf system in East Antarctica, the Amery Ice Shelf–Lambert Glacier system plays an important role in contributing to sea level rise as well as the surrounding environment and climate. The present study is focused on the investigation of surface melting over the ice shelf using QuikSCAT Ku-band scatterometer data for more than 100 months covering the period from January 2000 to July 2009. The corresponding weather data of Davis Station was obtained from the website of Australian Antarctic Division. Very prominent dips in the backscatter observed in the month of January form a distinct signature caused by physical process of significant melting of the ice/snow surface. The steep increase again in February is attributed to the initiation of the freezing phenomenon. The derived melting index compared well with the passive microwave-based melting index derived by other researchers. A strong relationship was found between the scatterometer-derived melting index and the cumulative monthly mean air temperature. The highest melting was observed in the summer (January) of 2004, and thereafter gradual cooling appeared to take place in the subsequent years. The snow pack thickness, inferred from the backscatter variations, was found to be higher during winters (June) of 2004 and 2005, compared with other years.

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Study of inter-annual variations in surface melting over Amery Ice Shelf, East Antarctica, using space-borne scatterometer data

In this paper, a thin ice thickness algorithm for coastal polynyas in the Chukchi and Beaufort Seas has been attempted which uses the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) 89-GHz brightness temperature data at a 6.25-km resolution. Thermal ice thickness estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) ice surface temperature data for a set of control points is used in conjunction with the AMSR-E brightness temperature data to develop a regression relationship between the thermal ice thickness and the passive microwave polarization ratio. The MODIS thermal ice thickness has been determined from the calculation of conductive heat flux through the ice-air interface. The relationship is then applied across the polynyas to derive thin ice thickness information at different points. In the development of the algorithm, the MODIS-derived thermal thickness is assumed to be the standard reference. Validation of the algorithm has been carried out using an independent MODIS-derived thermal ice thickness data set. It is observed that the model error is 1.3 cm within the thickness range of 1-10 cm. This method is expected to be useful in high latitudes where in situ observations are sparse.

Sandip R. Oza

Papers

Concurrent use of active and passive microwave remote sensing data for monitoring of rice crop

Spatial and temporal patterns of surface soil moisture over India estimated using surface wetness index from SSM/I microwave radiometer

Observing long-term changes in rice phenology using NOAA-AVHRR and DMSP-SSM/I satellite sensor measurements in Punjab, India

Study of inter-annual variations in surface melting over Amery Ice Shelf, East Antarctica, using space-borne scatterometer data

Estimation of Thin Ice Thickness From the Advanced Microwave Scanning Radiometer-EOS for Coastal Polynyas in the Chukchi and Beaufort Seas