Sugarcane (Saccharum officinarum L.) grows under different weather conditions directly affecting crop maturation. Raw material quality predicting models are important tools in sugarcane crop management; the goal of these models is to provide productivity estimates during harvesting, increasing the efficiency of strategical and administrative decisions. The objective of this work was developing ...

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in arid regions (especially in deserts) because of inaccurate remote sensing LST products. In this study, LST was downscaled by a random forest model between LST and ...

The study on soil spectral reflectance features is the physical basis for soil remote sensing. Soil organic matter content influences the soil spectral reflectance dramatically. This paper studied the spectral curves between 400nm~2500nm of 174 soil samples which were collected in Hengshan county and Yixing county. Fourteen types of transformation were applied to the soil reflectance R to remov...

Seepage zones have been shown to be of critical importance in controlling contaminant export from agricultural watersheds. To date, no multipurpose agricultural water quality model has seepage zones incorporated into its process-level representations. We chose to test two widely used models of agricultural water quality, the Groundwater Loading Effects of Agricultural Management Systems (GLEAMS...

Time series of Normalized Difference Vegetation Index (NDVI) derived from multiple satellite sensors are crucial data to study vegetation dynamics. The Land Long Term Data Record Version 4 (LTDR V4) NDVI dataset was recently released at a 0.05 × 0.05° spatial resolution and daily temporal resolution. In this study, annual NDVI time series that are composited by the LTDR V4 and Moderate Resoluti...

California growers face challenges with water shortages and there is a strong need to use the least amount of water while optimizing yield. Timely information on evapotranspiration (ET), a dominant component of crop consumptive water use, is critical for growers to tailor irrigation management based on in-field spatial variability and in-season variations. We evaluated the performance of a remo...

The advantages of using multispectral remotely sensed data instead of CORINE Land Cover for the modelling of nitrate concentrations in the leachate of the Rur catchment are presented and discussed in this paper. In this context it has been shown that the identification of main crops and annual crop rotation in the Rur catchment by SPOT, LANDSAT and ASTER imagery provides the key for a spatial a...

In this study, two kinds of numerical methods commonly used for estimating Weibull parameters are reviewed; i.e. the moment and energy trend factor method. Both methods used the coefficient of determination (R2) and root mean square error (RMSE) was compared with failure analysis. The statistical data of two years’ wind speed measurements of Nigde, Turkey, are used to find out the wind energy p...

Oilseed rape (Brassica napus L.) is one of the three most important oil crops in China, and is regarded as a drought-tolerant oilseed crop. However, it is commonly sensitive to waterlogging, which usually refers to an adverse environment that limits crop development. Moreover, crop growth and soil irrigation can be monitored at a regional level using remote sensing data. High spatial resolution...

The Ocean and Land Color Imager (OLCI) on the Sentinel-3A satellite, which was launched by the European Space Agency in 2016, is a new-generation water color sensor with a spatial resolution of 300 m and 21 bands in the range of 400–1020 nm. The OLCI is important to the expansion of remote sensing monitoring of inland waters using water color satellite data. In this study, we developed a dual b...