Writing01
Notes on GIS and remote sensing.
Worked examples in QGIS and Google Earth Engine, nearly all of them on real places. The settings and thresholds are written out, since those are usually where a map goes wrong.
RSS feed- 30 Oct 2026 · 9 minScreen VIIRS Fire Detections in QGIS for BandipurBandipur Tiger Reserve, Karnataka, India
- 28 Oct 2026 · 8 minA Cleaner HLS NDVI Series for Napa Valley VineyardsNapa Valley, California, United States
- 26 Oct 2026 · 9 minUse INSAT-3D Rainfall in QGIS for Konkan Storm ScreeningKonkan coast, Maharashtra, India
Where the posts are set
31 places · 39 India-wide
70° E80° E90° E10° N20° N30° NIndia-wide posts cover the country as a whole, or several places at once, so they have no single point.
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· 8 minUse India’s Landslide Atlas for Road Screening in QGISA cautious QGIS workflow for using India’s national landslide inventory near Gangtok, with practical checks that keep a screening map from becoming a false risk map.North Sikkim- · 9 minScreen VIIRS Fire Detections in QGIS for BandipurA practical QGIS method for turning NASA VIIRS detections into a defensible daily screening map for Bandipur, without treating each hotspot as a mapped fire perimeter.Bandipur Tiger Reserve, Karnataka
- · 8 minA Cleaner HLS NDVI Series for Napa Valley VineyardsBuild a cloud-screened vineyard NDVI series in QGIS with NASA’s Harmonized Landsat Sentinel-2 data, while avoiding false changes caused by mixed sensors and poor QA handling.Napa Valley, California
- · 9 minUse INSAT-3D Rainfall in QGIS for Konkan Storm ScreeningA practical QGIS method for using frequent INSAT-3D rainfall estimates to identify storm timing and catchment patterns along Maharashtra’s Konkan coast, without treating satellite pixels as rain gauges.Konkan coast, Maharashtra
· 9 minSentinel-2 Red-Edge in QGIS: Why 10 m Outputs MisleadA practical QGIS workflow for using Sentinel-2 red-edge bands without mistaking resampled 20 m information for genuine 10 m crop detail.Ludhiana, Punjab
· 6 minWhy Your GEE Water Area Total Is Wrong: Wular LakeA defensible Google Earth Engine workflow for measuring mapped open water at Wular Lake, with the scale, projection and threshold decisions made explicit.Wular Lake, Jammu and Kashmir
· 10 minMap Irrigation Canals in QGIS with Bhuvan WMSCreate a quality-checked canal inventory for the Krishna Delta by using Bhuvan web maps as reference imagery and topology-aware digitising in QGIS.Krishna Delta, Andhra Pradesh
· 8 minMap Mahanadi Sediment Plumes in QGIS with Sentinel-2 NDTIA practical QGIS workflow for screening relative turbidity patterns in the Mahanadi delta with Sentinel-2 surface reflectance, NDTI and careful water masking.Mahanadi Delta, Odisha
· 9 minMeasure Mangrove Area Reliably in QGIS: Bhitarkanika CRS WorkflowA practical QGIS workflow for calculating defensible mangrove polygon areas in Bhitarkanika, from checking CRS metadata to choosing ellipsoidal or projected measurements.Bhitarkanika, Odisha
· 8 minMask Terrain Shadows in Sentinel-2 for SikkimA practical Earth Engine workflow for separating terrain shadow from cloud shadow in Sentinel-2 surface reflectance before analysing Himalayan land cover.North Sikkim
· 7 minValidate a Bengaluru Land-Cover Map in Earth EngineA practical Google Earth Engine workflow for independently validating a Sentinel-2 land-cover map around Bengaluru, reading error matrices, and reporting credible accuracy metrics.Bengaluru, Karnataka
· 7 minMODIS EVI Anomalies in GEE for Nilgiris Tea LandscapesUse MODIS EVI and a seasonal baseline in Google Earth Engine to flag unusually low or high vegetation activity across the Nilgiris tea landscape.Nilgiris, Tamil Nadu
· 7 minMangrove Moisture Screening in QGIS with Sentinel-2 NDMIA careful QGIS workflow for using Sentinel-2 NDMI to screen relative canopy-moisture patterns in Bhitarkanika, with cloud masking, aligned pixels and defensible change checks.Bhitarkanika, Odisha
· 8 minStop Mixing Sentinel-1 Orbits in GEE: A Majuli WorkflowA practical Google Earth Engine workflow for making more defensible Sentinel-1 comparisons around Majuli by holding pass direction, relative orbit, mode and polarisation constant.Majuli, Assam
· 7 minSentinel-1 Terrain Effects in GEE for Western Ghats ForestsA practical guide to filtering Sentinel-1 GRD in Google Earth Engine, reading orbit and incidence-angle effects, and avoiding false forest-change signals in hilly Western Ghats terrain.Western Ghats, Karnataka
· 7 minSentinel-2 Bare Soil Index in GEE for Chambal RavinesA practical Google Earth Engine workflow for using Sentinel-2 Bare Soil Index to screen exposed soil and gully-prone ravine edges in the Chambal landscape.Chambal ravines, Madhya Pradesh
· 8 minIMD Tmax Grids in QGIS for Heatwave ScreeningA practical QGIS workflow for turning daily IMD maximum-temperature grids into simple heatwave screening maps, with threshold logic, masking tips, and beginner mistakes to avoid.Vidarbha, Maharashtra
· 7 minSentinel-2 NDSI Snow Mapping in GEE for GangotriA practical Google Earth Engine workflow for mapping seasonal snow around Gangotri using Sentinel-2 NDSI, cloud masking, elevation checks, and careful threshold validation.Gangotri, Uttarakhand
· 7 minSentinel-2 MCI in QGIS for Chilika Algal Bloom ScreeningA practical QGIS workflow for using Sentinel-2 red-edge bands and the Maximum Chlorophyll Index to screen possible algal bloom patches in Chilika Lake, Odisha.Chilika Lake, Odisha
· 7 minEOS-04 Soil Moisture in QGIS for Hisar Drought ScreeningA practical QGIS workflow for using ISRO EOS-04 surface soil moisture data to screen dry agricultural zones around Hisar, with validation cautions for beginners.Hisar, Haryana
· 7 minSentinel-1 RVI in GEE for Punjab Wheat VigourA practical Google Earth Engine workflow for using Sentinel-1 VV and VH radar backscatter to map wheat vigour in Punjab, including linear scaling, compositing, interpretation and beginner pitfalls.Punjab
· 6 minScaling Landsat Collection 2 in GEE for Delhi NDVIA practical Google Earth Engine workflow for applying Landsat Collection 2 scale factors, masking QA_PIXEL flags, and building reliable NDVI composites over Delhi's Yamuna floodplain.Delhi
· 8 minCGWB Groundwater Levels in QGIS for Jaipur MapsA practical QGIS workflow for turning CGWB groundwater level CSVs into cautious depth-to-water maps, using Jaipur and the dry Rajasthan fringe as the example area.Jaipur, Rajasthan
· 7 minLandsat QA_PIXEL Cloud Masking in GEE for Chambal RavinesA practical Google Earth Engine workflow for masking Landsat Collection 2 clouds, shadows and cirrus using QA_PIXEL before mapping vegetation in ravine landscapes.Chambal ravines, Madhya Pradesh
· 7 minSentinel-2 Shoreline Mapping in GEE for Pamban CoastA practical Google Earth Engine workflow for extracting a Sentinel-2 waterline around Pamban and Rameswaram, with cloud masking, NDWI thresholding, vector export, and field-aware cautions.Pamban and Rameswaram, Tamil Nadu
· 8 minIndia-WRIS River Gauge CSVs in QGIS for Monsoon HydrographsA practical guide to turning India-WRIS and National Water Data Portal river level CSVs into mapped station layers, monsoon hydrographs, and QA-ready flood-season notes in QGIS.Godavari Delta, Andhra Pradesh
· 10 minUsing Survey of India Open Series Maps in QGISA practical guide for Indian GIS learners on bringing Survey of India Open Series Maps into QGIS, choosing the right CRS, georeferencing scans, and checking accuracy before digitising.East Kolkata Wetlands, West Bengal
· 8 minResourcesat AWiFS NDVI Composites for Drought ScreeningA practical QGIS workflow for using Resourcesat AWiFS NDVI time composites to screen agricultural drought stress across Indian crop belts.Jalna, Maharashtra
· 7 minMapping Loktak Lake Open Water with Sentinel-2 MNDWIA practical Google Earth Engine workflow for mapping open water in Loktak Lake using Sentinel-2 surface reflectance, MNDWI, cloud masking and area summaries.Loktak Lake, Manipur
· 7 minBurn Severity Mapping with Sentinel-2 NBR in GEEA practical guide to mapping post-fire impact with Sentinel-2 surface reflectance, NBR and dNBR in Google Earth Engine, written for Indian GIS students and analysts.Similipal, Odisha
· 7 minMapping Rice Transplanting with Sentinel-1 VH in GEEA practical Sentinel-1 Google Earth Engine workflow for spotting rice transplanting signals in monsoon and samba paddy landscapes, with notes on VH backscatter, filtering, validation and beginner mistakes.Cauvery Delta, Tamil Nadu
· 8 minBhuvan LULC 50K in QGIS for Urban Fringe ScreeningA practical guide to using NRSC Bhuvan Land Use Land Cover 50K web services in QGIS for screening urban expansion around Indian city edges.Bengaluru, Karnataka
· 9 minIMD Gridded Rainfall in QGIS for Monsoon Anomaly MappingA practical QGIS workflow for turning IMD daily gridded rainfall NetCDF data into district-scale monsoon anomaly maps, using Kerala as a worked example.Kerala
· 9 minCartoDEM in QGIS for Slope Screening in the HimalayaA practical CartoDEM and QGIS workflow for Indian students who want to screen steep Himalayan terrain, create slope and hillshade layers, and avoid common DEM mistakes.Tehri, Uttarakhand
· 8 minNISAR GUNW in QGIS for Mining Subsidence MappingA practical guide to using NISAR geocoded unwrapped interferograms in QGIS, with a Jharia Coalfield workflow for line-of-sight displacement, coherence masking and beginner quality checks.Jharia, Jharkhand
· 7 minNDVI Thresholds for Land Cover Classification: What the Numbers MeanFixed NDVI thresholds borrowed from global studies routinely misclassify Indian land cover because soil background, monsoon phenology, and sensor differences each shift values by 0.1–0.2 or more. This article explains what NDVI actually encodes and how to build a more defensible classification workflow for India's ecologically diverse landscapes.
· 7 minRISAT-2B SAR: Bands, Modes and Applications for Indian UsersRISAT-2B is ISRO's X-band SAR satellite that complements Sentinel-1 for Indian applications, this article breaks down its imaging modes, frequency trade-offs, and where it genuinely outperforms C-band sensors for flood mapping, crop monitoring, and coastal work.
· 6 minSAR Backscatter for Soil Moisture: Sentinel-1 Methods ExplainedA technical walkthrough of how Sentinel-1 C-band SAR backscatter is used to estimate soil moisture across Indian agricultural land, covering the physics, key retrieval algorithms, and practical pitfalls.
· 6 minFlow Accumulation and Stream Order from DEM in QGIS: Step by StepA step-by-step QGIS walkthrough of flow accumulation and stream ordering from a DEM, covering sink filling, flow direction, and common mistakes that silently break watershed delineation in Indian study areas.
· 7 minEstimating Crop Yield with SAR and Optical Data Fusion in GEECloud cover during India's kharif season makes optical-only yield models unreliable. This article shows how to fuse Sentinel-1 SAR and Sentinel-2 data in Google Earth Engine to build a cloud-robust crop yield estimation workflow.
· 7 minFlood Depth Estimation from Sentinel-1 SAR: Methods and LimitsFlood extent mapping from Sentinel-1 SAR is now routine, but translating backscatter into actual water depths is far harder. This article breaks down the main methods, hydraulic model fusion, DEM differencing, and their real limits, for Indian flood contexts.
· 6 minGRACE-FO vs GRACE: What Changed for Groundwater MonitoringGRACE-FO introduced laser ranging and improved accelerometers over its predecessor, but instrument upgrades and a one-year data gap create real methodological challenges for anyone building long-term groundwater depletion records over India.
· 7 minSUHI vs RUHI: Separating Surface and Air Temperature in UHI StudiesSUHI measures radiative skin temperature from satellites; conventional UHI measures screen-level air temperature. Conflating the two leads to flawed mitigation policy in Indian cities where ground-truth met data is scarce.
· 7 minRTK vs PPK GNSS: Choosing the Right Mode for Drone SurveysRTK and PPK both deliver centimetre-level GNSS accuracy for drone surveys, but the right choice depends on your data link reliability, terrain, and post-processing workflow, a decision that matters especially across India's varied field conditions.
· 7 minGround Sampling Distance Explained: How GSD Affects Map AccuracyGround sampling distance (GSD) sets the resolution ceiling for every drone survey output. This article explains the GSD formula, application-specific thresholds for Indian projects, and the most common field mistakes that make datasets unusable.
· 7 minNetwork Analysis in QGIS: Shortest Path and Service Area ToolsA practical guide to network analysis in QGIS covering shortest path routing and service area tools, with India-specific data preparation steps, a Nagpur worked example, and guidance on the QNEAT3 plugin for isochrone generation.
· 6 minExporting Large GEE Results to Google Drive Without Hitting LimitsGEE exports silently fail at scale because of pixel count limits, file size constraints, and Drive storage quirks. This post explains spatial tiling, key export parameters, and when to switch from Drive to Cloud Storage for large-area workflows.
· 7 minLandsat Surface Temperature: Retrieving LST from Band 10 Step by StepA step-by-step technical walkthrough of Landsat LST retrieval from Band 10, covering DN-to-radiance conversion, brightness temperature, NDVI-based emissivity estimation, and where calibration errors cost you several degrees Celsius.
· 7 minSentinel-2 Atmospheric Correction: DOS vs Sen2Cor vs ACOLITEChoosing the wrong atmospheric correction method can silently bias every NDVI, land cover, or water quality result you derive from Sentinel-2. This article compares DOS, Sen2Cor, and ACOLITE against the aerosol and humidity conditions typical of India and South Asia.
· 6 minRandom Forest vs SVM for LULC Classification: Which Wins in GEE?A direct comparison of Random Forest and SVM for LULC classification in Google Earth Engine, using Indian landscape challenges, class imbalance, monsoon cloud cover, and spectral confusion, to show where each algorithm actually wins.
· 6 minMapping Reservoir Storage Changes with NDWI and Landsat in GEEA step-by-step guide to mapping seasonal reservoir storage changes across India using NDWI and Landsat imagery in Google Earth Engine, with honest notes on turbidity, cloud shadow, and threshold validation.
· 7 minNDVI Time-Series Analysis in GEE: Detecting Seasonal Crop CyclesA technical walkthrough of building NDVI time-series workflows in Google Earth Engine to detect kharif, rabi, and zaid crop cycles across Indian agricultural landscapes, covering collection setup, cloud masking, and phenology curve extraction.
· 7 minResourcesat-2A LISS-IV Explained: Bands, Resolution and Use CasesA practitioner-oriented reference explaining Resourcesat-2A LISS-IV's spectral bands, 5.8 m resolution, and how it compares to Sentinel-2 and Landsat for India-specific mapping workflows.
· 7 minSAR Coherence for Landslide Mapping: Sentinel-1 Methods ExplainedSAR coherence change detection lets disaster managers map monsoon landslides in the Himalayas and Western Ghats even under total cloud cover. This article walks through the full Sentinel-1 SLC processing workflow in SNAP and explains where the method succeeds and fails in Indian terrain.
· 7 minDEM Vertical Accuracy: SRTM vs ALOS vs Copernicus ComparedA technical comparison of SRTM, ALOS AW3D30, and Copernicus DEM vertical accuracy across India's diverse terrain, with a decision framework for watershed delineation, flood mapping, and landslide modelling.
· 6 minCrop Water Stress Mapping with Sentinel-2 NDWI and NDRE in GEENDVI lags crop water stress by days that cost yield. This article shows how to map early stress across the Indo-Gangetic Plain using Sentinel-2 NDWI and NDRE in Google Earth Engine, with step-by-step GEE code.
· 7 minOptical vs SAR Flood Mapping: Choosing the Right Satellite DataSAR or optical imagery for flood mapping in India? This article breaks down the decision logic, cloud cover, terrain, timing, and use case, with evidence from Sentinel-1 and Sentinel-2 studies across Indian flood-prone regions.
· 6 minDetecting Saltwater Intrusion in Coastal Aquifers with Remote SensingA practical walkthrough of how satellite sensors, InSAR, and EMI surveys detect saltwater intrusion in India's coastal aquifers across Gujarat, Tamil Nadu, Kerala, and Odisha, and where each method's limits lie.
· 7 minMapping Urban Heat Islands with Landsat LST in Google Earth EngineA practical GEE workflow for mapping urban heat islands using Landsat 8 LST in Delhi NCR, covering NDVI-based emissivity estimation, Band 10 brightness temperature conversion, and the full LST retrieval formula.Delhi
· 7 minGNSS Jamming and RTK Surveys: What Field Teams Must KnowGNSS jamming and spoofing are growing threats to RTK and PPK surveys in India. This guide explains how interference breaks carrier-phase positioning and what field teams can do to detect and recover from it.
· 7 minDrone Surveys for Waste Quantification: Methods and AccuracyA technical walkthrough of drone photogrammetry workflows for legacy waste quantification in India, using the Bandhwari landfill survey as a case study, covering GCPs, GSD, and realistic volume accuracy.
· 6 minWatershed Delineation in QGIS Using SRTM DEM: Step by StepA step-by-step QGIS workflow for watershed delineation using free SRTM 30 m DEM, covering sink filling, flow direction, flow accumulation, stream extraction, and pour-point snapping, with India-specific guidance on where the process commonly fails.
· 5 minMapping Soil Salinity in GEE: Indices, Datasets and CodeA practical guide to mapping soil salinity in Google Earth Engine using validated spectral indices, Sentinel-2 and Landsat datasets, and code patterns tuned for India's Indo-Gangetic Plain and coastal deltas.
· 7 minLandsat Band Combinations: Which to Use and WhenA practical reference guide to Landsat 8 and 9 band combinations, natural color, false color, agriculture, and more, with Indian landscape contexts including the IGP, Punjab croplands, and Deccan scrub.
· 7 minSentinel-2 Cloud Masking: SCL Band vs. s2cloudless ComparedA technical comparison of Sentinel-2's built-in SCL band and the s2cloudless ML model for cloud masking, with a focus on Indian monsoon conditions where cloud cover disrupts agricultural monitoring and flood mapping.
· 6 minRed Edge Indices for Crop Stress Detection: Beyond NDVIRed edge indices like NDRE and CIre detect crop stress weeks before NDVI saturates, here is how to apply them on Sentinel-2 imagery for Indian wheat and rice fields.
· 7 minSAR Flood Mapping with Sentinel-1: How It Works and Why It Matters for IndiaSAR flood mapping with Sentinel-1 works through microwave backscatter contrast between water and land, and with India's new ISRO-Jal Shakti MOU, it is moving from research into operational policy. Here is how the technique actually works, step by step.
· 7 minHow GRACE Satellites Measure Groundwater Loss Beneath Your FeetGRACE and GRACE-FO satellites measure tiny changes in Earth's gravitational field to track groundwater depletion from orbit, a method now central to water-resource monitoring in India and globally.
· 6 minReading NDVI: turning Sentinel-2 into vegetation insightNDVI turns red and near-infrared bands into a simple measure of how green and healthy vegetation is. Here is how I compute and read it from Sentinel-2 and Landsat in my Punjab and Delhi NCT work.
· 7 minGCPs and GNSS: how to get drone maps to line upA practical guide to ground control points and GNSS for accurate drone maps, drawn from my UAV photogrammetry work at IIT Roorkee using Emlid Reach RS3 and Trimble DA.
· 7 minBuffer analysis and zonal statistics in QGIS, explainedA practical guide to buffer zones and zonal statistics in QGIS for measuring environmental footprint, grounded in my Delhi NCT industrial impact work with Sentinel-2 indices.Delhi
· 6 minQGIS vs ArcGIS Pro: which GIS tool should you learn?An honest practitioner comparison of QGIS and ArcGIS Pro for GIS and remote sensing work, with cost, workflow, and practical advice for students in India.
· 7 minNDWI and NDBI explained: mapping water and built-up landA plain guide to NDWI and NDBI: the formulas, band pairs, and how I read them alongside NDVI to map water, moisture, and built-up land in India.
· 6 minGroundwater depletion in Punjab: what 25 years of satellite data revealPunjab grows much of India's grain but is draining its aquifers fast. Here is how Landsat NDVI and NDWI change maps over 2000-2025, paired with groundwater data, expose the stress.Punjab
· 6 minSentinel-2 bands explained: a practical beginner guideA plain, practical guide to Sentinel-2 bands, their 10/20/60 m resolutions, and which bands to use for NDVI, NDWI, and NDBI, with free Copernicus access.
· 7 minDrone photogrammetry step by step: from flight plan to orthomosaicA field-tested guide to UAV photogrammetry, from flight planning and ground control to processing an orthomosaic, DSM, and point cloud, drawn from my survey work at IIT Roorkee.Roorkee, Uttarakhand
· 7 minHow to start a career in GIS and remote sensing in IndiaA practical roadmap to break into GIS and remote sensing in India: degrees, QGIS and ArcGIS, Python, Google Earth Engine, Esri and IIRS/ISRO certifications, projects, and where to find jobs.
· 7 minGoogle Earth Engine: cloud remote sensing for everyoneGoogle Earth Engine puts decades of satellite data and planetary-scale processing in your browser. Here is what it is, why it matters, and how to start.