Monitoring changes in carbon stocks through forest biomass assessment is crucial for cycle studies. However, challenges obtaining timely and reliable ground measurements hinder creation of the spatially continuous maps aboveground density (AGBD). This study proposes an approach generating (AGBD) by combining Global Ecosystem Dynamics Investigation (GEDI) LiDAR-based data with open-access earth observation (EO) data. The key contribution lies systematic evaluation various model configurations...

Abstract. The main objective of this study is the in-season forecasting soybean crop yield using integration satellite remote sensing and weather observations. was carried out in Paran´a state Brazil. region sown during Oct.–Nov. month harvested between Feb.–Mar. next year. Municipality-level data for 15 municipalities obtained from AGROLINK portal Brazil, 2005–06 season to 2020–21 season. constituted yearly municipality-wise kg/ha. Remote sensing-based indicators such as Normalized...

With advances in sensing systems attempts are continuously being made to design Internet of Things (IoT) based interoperable systems. The important issues (water, pest/disease, nutrient management, etc.) pertaining crop-weather-soil continuum can be addressed through high resolution monitoring agro-meteorological parameters. Presently the designed have syntactic and semantic heterogeneity face underlying limitations for achieving interoperability among these distributed In this study an...

Abstract. Spatio-temporal crop phenological information helps in understanding trends food supply, planning of seed/fertilizer inputs, etc. a region. Rice is one the major sources for many regions world especially monsoon Asia and accounts more than 11 % global cropland. Accurate, on-time early on spatial distribution rice would be useful stakeholders (cultivators, fertilizer/pesticide manufacturers agriculture extension agencies) to effectively plan supply market activities. Also,...

Natural calamities triggered by erratic weather conditions like cyclone, earthquakes, hail storms, and flood incurs substantial loss to the infrastructure crops of region. Countries across globe are prone such natural calamities. In India, specifically coastal parts vulnerable tropical cyclones. 2018 east coast districts Tamil Nadu Andhra Pradesh, India were affected three cyclones namely Titli (11 Oct. 2018), Gaja (16 Nov. 2018) Pethai (17 Dec. causing severe damage seasonal as Rice,...

Abstract. The current study focuses on the estimation of cloud-free Normalized Difference Vegetation Index (NDVI) using Synthetic Aperture Radar (SAR) observations obtained from Sentinel-1 (A and B) sensor. South-West Summer Monsoon over Indian sub-continent lasts for four months (mid-June to mid-October). During this time, optical remote sensing are affected by dense cloud cover. Therefore, there is a need methodology estimate state vegetation during crops considered in Paddy (Rice) Punjab...

Crop water stress is one of the major factors limiting crop productivity. Maize (Corn) very sensitive to stress. Efficient monitoring and detection crucial for precision irrigation sustainable agriculture. The main objective this study detect during grain-fill stage in maize crops using hyperspectral (HS) observations. hybrid field trial plots were selected from Hyderabad region, Telangana, India. HS images area collected a hexacopter drone mounted with line scanning camera having spectral...

The Traffic problems are a critical problem that influences the travel time of vehicles. road conditions affecting smooth movement vehicles increases traffic issue also unorganized flow, no dividers, steep curves, etc. gives birth to accidents. Lack information shortest path affects emergency vehicle routing. Although calamities, accidents or casualties subject factors cannot be predetermined, an precautionary measures can play crucial role avoid same. aim this work is develop GIS based...

Synthetic aperture radar (SAR) remote sensing has been widely used for crop monitoring due to its high-resolution imaging and all-weather data acquisition capabilities. In this study, time-series interferometric SAR (InSAR) coherence products generated from Sentinel-1 were employed monitor phenological stages, determine total cropping duration estimate sowing as well harvest dates the Bengal-gram crop. The was cultivated in study region lies Chhattisgarh, India, during Rabi 2018–2019 season....

Abstract. Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one oldest sources EO datasets. This historical near real time archive a rich source information understand seasonal in horticultural crops. Citrus (Mandarin / Nagpur Orange) major crops cultivated...

Spatio-temporal root zone soil moisture (STRZSM) plays a vital role in the understanding of land-surface dynamics, climate change, soil-water-balance, hydrologic processes, vegetation growth and yield modeling. STRZSM trails can be captured using remote sensing, in-situ or ground based measurements through land surface models. Apart from this, new generation low-cost sensors present cost effective way measurement moisture, but suffer inherent heterogeneity between sensing techniques,...

Abstract. In season crop area mapping is of significant importance for multiple reasons such as monitoring if health and residue burning areas, etc. Wheat one the important cereal cultivated all across India, with Punjab-Haryana being prime contributors to total production. this study we propose a method early using combined use temporal Sentinel-1 2 observations. Further, estimate phenology parameter viz. sowing date time series Normalized Difference Vegetation Index (NDVI). Few districts...

Rice is a staple food across the majority of world's population that expected to exceed 9 billion by 2050 and will require approximately 60% more food. In season accurate information on spatiotemporal distribution rice cultivation, phenology region spatial yield significant importance. This used various stakeholders such as government, policymakers, insurance companies, agri-input companies. Methods involving manual surveys for developing crop are constrained short harvest window...

Soil moisture is an important variable in the agriculture system. Likewise, accurate information on soil needed for effective modeling of many hydrological and climatological processes. Synthetic Aperture Radar (SAR) operates with competence to acquire data any weather condition, has been proved be sensitive surface moisture. This study attempted establish simple experimental relationships estimate volumetric bare (smv) using SAR satellite-based radar backscatter values (σ°). In this study,...

Abstract. The Normalized Difference Vegetation Index (NDVI) is a useful index for vegetation monitoring. However, due to cloud cover the observations of NDVI are discrete and vary in intensity. Therefore, there need estimate during using alternative sources satellite observations. main objective this study cloudy conditions moderate resolution multi-spectral synthetic aperture radar (SAR) Two approaches were identified: 1) pixel replacement 2) machine learning based regression analysis free...

Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one oldest sources EO datasets. This historical near real time archive a rich source information understand seasonal in horticultural crops. Citrus (Mandarin / Nagpur Orange) major crops cultivated central...

Abstract. Rapid advances in Wireless Sensor Network (WSN) for agricultural applications has provided a platform better decision making crop planning and management, particularly precision agriculture aspects. Due to the ever-increasing spread of WSNs there is need standards, i.e. set specifications encodings bring multiple sensor networks on common platform. Distributed systems when brought together can facilitate domain. The Open Geospatial Consortium (OGC) through Web Enablement (SWE)...

To monitor changes in the landscapes at local to regional scales, a large amount of multi-temporal remote sensing products are required for analysis. Due frequent need sensing-based results, research as well commercial organizations automated, faster and more efficient methods downloading subsequently, processing enormous such datasets. In this study, we have designed developed geospatial data frameworks enriched with automated search, download, Sentinel-1,-2 data. The analysis-ready outputs...

Abstract. The main objective of this study is the spatial downscaling Soil Moisture Active Passive (SMAP) soil moisture (36 km) using Moderate Resolution Imaging Spectroradiometer (MODIS) and Shuttle Radar Topography Mission (SRTM) products. was conducted over India during post-monsoon (i.e., Rabi) season Daily SMAP (SM) data composited to 3 days cover entire area. MODIS for Normalized Difference Vegetation Index (NDVI), Water (NDWI), Albedo, Land Surface Temperature (LST) were similarly...