Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate dail...
Recently, the United States Geological Survey (USGS) has released a new dataset, called Landsat Analysis Ready Data (ARD), which is designed specifically for facilitating time series analysis. In this study, we evaluated the temporal consistency of t...
Data that have been processed to allow analysis with a minimum of additional user effort are often referred to as Analysis Ready Data (ARD). The ability to perform large scale Landsat analysis relies on the ability to access observations that are geo...
Land surface temperature (LST) is a critical state variable of land surface energy equilibrium and a key indicator of environmental change such as climate change, urban heat island, and freezing-thawing hazard. The high spatial and temporal resolutio...
Ever increasing data volumes of satellite constellations call for multi-sensor analysis ready data (ARD) that relieve users from the burden of all costly preprocessing steps. This paper describes the scientific software FORCE (Framework for Operation...
The multi-decadal Landsat data record is a unique tool for global land cover and land use change analysis. However, the large volume of the Landsat image archive and inconsistent coverage of clear-sky observations hamper land cover monitoring at larg...
The recently available Landsat Analysis Ready Data (ARD) are provided as top of atmosphere (TOA) and atmospherically corrected (surface) reflectance tiled products and are designed to make the U.S. Landsat archive for the United States straightforwar...
In the face of global ocean warming, monitoring essential climate variables from space is necessary for understanding regional trends in ocean dynamics and their subsequent impacts on ecosystem health. Analysis Ready Data (ARD), being preprocessed sa...
An approach to remove clouds in Landsat-8 operational land imager (OLI) data was developed with independent component analysis (ICA). Within cloud-covered areas, histograms were derived to quantify changes of the reflectance values before and after t...
High-quality Normalized Difference Vegetation Index (NDVI) time series are essential in studying vegetation phenology, dynamic monitoring, and global change. Gap filling is the most important issue in reconstructing NDVI time series from satellites w...
Drylands are the habitat and source of livelihood for about two fifths of the world’s population and are highly susceptible to climate and anthropogenic change. To understand the vulnerability of drylands to changing environmental conditions, l...
Rice is an important food resource, and the demand for rice has increased as population has expanded. Therefore, accurate paddy rice classification and monitoring are necessary to identify and forecast rice production. Satellite data have been often...
Time series from Landsat and Sentinel-2 satellites have great potential for modeling vegetation seasonality. However, irregular time sampling and frequent data loss due to clouds, snow, and short growing seasons, makes this modeling a challenge. We d...
Monitoring the lake waterbody area in the Qinghai–Tibet Plateau (QTP) is significant in dealing with global climate change. The latest released Landsat-9 data, which has higher radiation resolution and can be complemented with other Landsat dat...
The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS...
After Landsat 8 was launched in 2013, it was observed that for Thermal Infrared sensor (TIRS) bands, radiance from outside of an instrument’s field-of-view produced a non-uniform ghost signal across the focal plane that varied depending on the out-of...
Major development projects along rivers, like reservoirs and other hydraulic structures, have changed not only river discharges but also sediment transport. Thus, changes in river planforms can be observed in such rivers. In addition, river centerlin...
As the world urbanizes and builds more infrastructure, the extraction of built-up areas using remote sensing is crucial for monitoring land cover changes and understanding urban environments. Previous studies have proposed a variety of methods for ma...
Most of the lakes in Indonesia are facing environmental problems such as eutrophication, sedimentation, and depletion of dissolved oxygen. The water quality data for supporting lake management in Indonesia are very limited due to financial constraint...
The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated...
Despite its wide applications, the spatiotemporal fusion of coarse- and fine-resolution satellite images is limited primarily to the availability of clear-sky fine-resolution images, which are commonly scarce due to unfavorable weather, and such a li...
Clay content (fraction < 2 µm) is one of the most important soil properties. It controls soil hydraulic properties like wilting point, field capacity and saturated hydraulic conductivity, which in turn control the various fluxes of water in the un...
Classifying remote sensing imageries to obtain reliable and accurate land use and land cover (LULC) information still remains a challenge that depends on many factors such as complexity of landscape, the remote sensing data selected, image processing...
Forest stock volume (FSV) is a key indicator for measuring forest quality, evaluating forest management capabilities, and the main factor for evaluating forest carbon sequestration levels. In this study, to achieve an accurate estimation of FSV, we u...
In the face of global population growth and climate change, the protection and rational utilization of cropland are crucial for food security and ecological balance. However, the complex topography and unique ecological environment of the Qinghai-Tib...
The successful launch of the Landsat 8 satellite with two thermal infrared bands on February 11, 2013, for continuous Earth observation provided another opportunity for remote sensing of land surface temperature (LST). However, calibration notices is...
The Landsat 8 satellites have retrieved land surface temperature (LST) resampled at a 30-m spatial resolution since 2013, but the urban climate studies frequently use a limited number of images due to the problems related to missing data over the cit...
The Landsat Analysis Ready Data (ARD) are designed to make the U.S. Landsat archive straightforward to use. In this paper, the availability of the Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) ARD over the co...
In recent years, the vegetation cover in urban agglomerations has been changing very rapidly due to technogenic influence. Satellite images play a huge role in studying the dynamics of forest vegetation. Special programs are used to process satellite...
Accurate crop yield assessments using satellite remote sensing-based methods are of interest for regional monitoring and the design of policies that promote agricultural resiliency and food security. However, the application of current vegetation pro...
Lake Clark is an important nursery lake for sockeye salmon (Oncorhynchus nerka) in the headwaters of Bristol Bay, Alaska, the most productive wild salmon fishery in the world. Reductions in water clarity within Alaska lake systems as a result of incr...
The Google Earth Engine (GEE) has emerged as an essential cloud-based platform for land-cover classification as it provides massive amounts of multi-source satellite data and high-performance computation service. This paper proposed an automatic land...
A quantitative assessment of forest cover change in the Moulouya River watershed (Morocco) was carried out by means of an innovative approach from atmospherically corrected reflectance Landsat images corresponding to 1984 (Landsat 5 Thematic Mapper)...
The recently released Landsat analysis ready data (ARD) over the United States provides the opportunity to investigate landscape dynamics using dense time series observations at 30-m resolution. However, the dataset often contains data gaps (or missi...
Current methods for monitoring deforestation from satellite data at sub-annual scales require pixel time series to have many historical observations in the reference period to model normal forest dynamics before detecting deforestation. However, in s...
Water temperature is a key element of freshwater ecological systems and a critical element within natural resource monitoring programs. In the absence of in situ measurements, remote sensing platforms can indirectly measure water temperature over tim...
This study aims to investigate how alternations of the land surface temperature (LST) affects the normalized difference vegetation index (NDVI) in Paphos forest, Cyprus, using Landsat-5 and Landsat-8 imagery for the time periods 1993–2000 and 2...
The methods for accurately fusing medium- and high-spatial-resolution satellite reflectance are vital for monitoring vegetation biomass, agricultural irrigation, ecological processes and climate change. However, the currently existing fusion methods...
To effectively monitor the spatio–temporal dynamics of the surface water extent (SWE) in Lake Victoria, this study introduced a novel methodology for generating a seamless SWE time series with fine resolution by integrating daily a Moderate-res...
Climate change poses a disproportionate risk to alpine ecosystems. Effective monitoring of forest phenological responses to climate change is critical for predicting and managing threats to alpine populations. Remote sensing can be used to monitor fo...
Accurate monitoring of grassland biomass at high spatial and temporal resolutions is important for the effective utilization of grasslands in ecological and agricultural applications. However, current remote sensing data cannot simultaneously provide...
Mangrove forests play a global role in providing ecosystem goods and services in addition to acting as carbon sinks, and are particularly vulnerable to climate change effects such as rising sea levels and increased salinity. For this reason, accurate...
Accurate, spatially explicit information about forest canopy fuel properties is essential for ecosystem management strategies for reducing the severity of forest fires. Airborne LiDAR technology has demonstrated its ability to accurately map canopy f...
Despite increasing the number of studies for mapping remote sensing insect-induced forest infestations, applying novel approaches for mapping and identifying its triggers are still developing. This study was accomplished to test the performance of Ge...
Land surface temperature (LST) plays a pivotal role in many environmental sectors. Unfortunately, thermal bands produced by instruments that are onboard satellites have limited spatial resolutions; this seriously impairs their potential usefulness. I...
Analysis of urban land use dynamics is essential for assessing ecosystem functionalities and climate change impacts. The focus of this study is on monitoring the characteristics of urban expansion in Hang-Jia-Hu and evaluating its influences on fores...
An approach based on the nearest neighbors techniques is presented for producing thematic maps of forest cover (forest/non-forest) and total stand volume for the Terai region in southern Nepal. To create the forest cover map, we used a combination of...
Crop type information at the field level is vital for many types of research and applications. The United States Department of Agriculture (USDA) provides information on crop types for US cropland as a Cropland Data Layer (CDL). However, CDL is only...
Long revisit intervals and cloud susceptibility have restricted the applicability of earth observation satellites in surface water studies. Integrating multiple satellites offers potential for more frequent observations, yet combining different satel...
Estimating forest area at a national scale within the United Nations program of Reducing Emissions from Deforestation and Forest Degradation (REDD) is primarily based on land cover information using remote sensing technologies. Timely delivery for a...
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